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Technology and employment in the food and drink industries
Report for discussion at the, Technology and Employment in the Food and Drink Industries
Copyright ® 1999 International Labour Organization (ILO)
3. Impacts
of new technology
on employment
Over the past 200 years millions of jobs have been replaced by machines. However, in industrialized countries primarily, there has also been a continuous increase in job numbers and in real incomes, not in spite of technological change, but because of it. New technology may reduce the number of existing jobs, but many studies show that it creates new demand, "either by increasing productivity and hence real incomes, or by creating new goods".(1)
Technological change is double-edged; it both destroys jobs and creates new ones. Economists have generally argued that in the long run new technology creates more jobs than it eliminates. However, compensation may not be automatic, painless or instantaneous; there may be lags between the time when jobs are replaced by machines and the time when new ones are created. Those who have been made redundant may not be qualified for the new jobs that are be created. Furthermore, new jobs may be created in locations to which it may not be practical for many people to move for various reasons.(2) This section will examine employment trends in the FD industries in general as well as in some specific cases against the backdrop of the rapid technological developments seen in recent years. It will also look into how new technology may have influenced both forms of employment and skill requirements.
Tables 3.1 and 3.2 present employment figures in the food and drink industries respectively for selected countries and territories for the period 1985-95. Although the data are incomplete, the tables show that employment has declined gradually in many high-income and upper middle-income countries in both the food and drink industries, while it has increased in many low-income and lower middle-income countries. Since high-income and upper middle-income countries are likely to have adopted more labour-saving technology than lower-income ones, their employment decline may have been largely due to this factor. However, other factors, such as the greater maturity of FD industries in high-income countries, were also at work. That the decline was not entirely determined by new technology is shown by the example of the United States where the food industry workforce grew continuously until 1993.
The rate of decline in the drink industry appears to have been greater than that in the food industry, particularly among high-income countries. As the drink industry lends itself more easily than the food industry to the substitution of capital for labour, this factor is likely to have been responsible for the higher decline in employment seen in this industry.
Tables 3.3 and 3.4 present employment in the food and drink industries respectively as a percentage of employment in total manufacturing in selected countries and territories for the period 1985-95. Table 3.3 indicates that the proportion of the food-processing workforce within total manufacturing has been growing in many industrialized and upper middle-income countries. This suggests that the substitution of capital for labour has proceeded more rapidly in other manufacturing sectors than in the food industry, thus the employment decline has been greater in the former.
On the other hand, in many lower-income countries the percentage of food workers in total manufacturing has declined despite the fact that the absolute number of workers has increased (table 3.1). These countries are now experiencing relatively rapid economic growth, and other manufacturing sectors are experiencing faster employment growth than the food industry.
Table 3.1. Employment in
food products (ISIC 311), 1985-95
Country/territory |
1985 |
1986 |
1987 |
1988 |
1989 |
1990 |
1991 |
1992 |
1993 |
1994 |
1995 |
High-income non-OECD |
|||||||||||
Cyprus |
4 686 |
4 873 |
5 063 |
5 404 |
5 686 |
5 880 |
5 833 |
5 988 |
5 945 |
6 392 |
6 546 |
Hong Kong |
18 500 |
18 900 |
19 300 |
19 600 |
18 700 |
21 000 |
21 300 |
20 800 |
20 400 |
||
Israel |
41 700 |
43 640 |
48 500 |
48 600 |
44 600 |
42 000 |
43 600 |
43 300 |
45 300 |
48 941 |
|
Kuwait |
6 280 |
6 485 |
6 875 |
7 214 |
7 075 |
7 727 |
4 791 |
5 953 |
6 744 |
6 759 |
6 699 |
Singapore |
9 686 |
9 622 |
10 181 |
10 400 |
10 391 |
10 615 |
11 104 |
11 565 |
11 874 |
11 800 |
11 855 |
High-income OECD |
|||||||||||
Australia |
143 700 |
144 000 |
145 000 |
151 000 |
153 000 |
150 000 |
148 000 |
146 000 |
|||
Austria |
53 200 |
51 800 |
51 800 |
51 600 |
51 200 |
52 800 |
51 000 |
51 000 |
49 955 |
49 018 |
49 029 |
Belgium |
74 000 |
73 300 |
73 100 |
74 500 |
75 800 |
75 800 |
76 100 |
75 300 |
|||
Canada |
190 300 |
195 100 |
197 000 |
201 000 |
201 900 |
197 800 |
192 000 |
195 000 |
189 000 |
189 000 |
189 213 |
Denmark |
66 343 |
67 697 |
66 892 |
64 500 |
63 100 |
87 371 |
85 561 |
83 181 |
|||
Finland |
51 162 |
50 468 |
50 214 |
49 500 |
47 300 |
46 600 |
44 700 |
41 400 |
38 500 |
36 200 |
35 667 |
France |
461 400 |
462 400 |
463 100 |
463 100 |
463 700 |
462 500 |
459 100 |
454 100 |
449 500 |
||
Germany |
511 000 |
448 787 |
442 445 |
||||||||
Germany (former FRG) |
335 201 |
334 928 |
337 588 |
339 207 |
354 077 |
376 275 |
403 089 |
401 500 |
|||
Iceland |
13 399 |
13 773 |
14 270 |
12 528 |
11 921 |
11 200 |
10 891 |
9 982 |
9 982 |
10 399 |
|
Ireland |
38 900 |
38 000 |
37 312 |
37 300 |
36 600 |
36 700 |
37 500 |
36 227 |
35 534 |
34 581 |
33 266 |
Italy |
155 000 |
145 000 |
149 000 |
163 102 |
157 503 |
162 655 |
164 443 |
162 966 |
162 966 |
||
Japan |
1 030 000 |
1 066 000 |
1 077 000 |
1 095 000 |
1 101 000 |
1 138 000 |
1 153 000 |
1 165 000 |
1 185 000 |
1 147 000 |
1 145 000 |
Luxembourg |
2 203 |
2 248 |
2 283 |
2 272 |
2 440 |
2 472 |
2 722 |
2 799 |
2 974 |
2 868 |
|
Netherlands |
113 000 |
113 000 |
116 103 |
106 303 |
106 532 |
107 759 |
110 073 |
109 732 |
107 699 |
107 000 |
108 243 |
New Zealand |
67 124 |
66 740 |
60 200 |
59 890 |
59 637 |
56 464 |
56 044 |
57 604 |
58 971 |
||
Norway |
47 233 |
47 610 |
47 500 |
46 000 |
44 800 |
43 906 |
43 580 |
39 967 |
40 063 |
40 986 |
41 163 |
Spain |
228 285 |
226 140 |
232 811 |
252 494 |
255 368 |
258 596 |
264 061 |
264 038 |
264 509 |
266 353 |
265 439 |
Sweden |
62 200 |
63 200 |
62 800 |
63 300 |
63 700 |
61 500 |
62 861 |
58 908 |
56 205 |
54 493 |
|
Switzerland |
71 600 |
72 000 |
72 800 |
73 700 |
75 100 |
74 300 |
70 800 |
69 100 |
70 700 |
||
United Kingdom |
487 000 |
487 000 |
499 000 |
498 000 |
504 000 |
503 000 |
490 000 |
482 000 |
479 480 |
477 000 |
474 560 |
United States |
1 249 000 |
1 248 000 |
1 300 000 |
1 314 000 |
1 315 000 |
1 333 000 |
1 339 000 |
1 369 000 |
1 385 000 |
1 383 000 |
1 382 520 |
Low-income |
|||||||||||
Bangladesh |
45 700 |
46 055 |
48 498 |
51 132 |
125 943 |
110 686 |
104 187 |
106 167 |
|||
Burundi |
631 |
1 068 |
1 068 |
1 068 |
1 411 |
1 620 |
|||||
Cambodia |
12 807 |
12 061 |
11 780 |
10 828 |
8 700 |
8 810 |
11 208 |
||||
Central African Republic |
663 |
576 |
488 |
464 |
428 |
558 |
532 |
472 |
|||
China |
2 319 000 |
2 475 000 |
2 593 000 |
2 750 000 |
2 720 000 |
3 050 000 |
3 210 000 |
3 270 000 |
3 130 000 |
3 180 000 |
|
Egypt |
148 216 |
151 236 |
173 692 |
175 656 |
188 933 |
204 200 |
243 000 |
193 000 |
210 242 |
216 391 |
|
Ghana |
7 295 |
7 606 |
12 264 |
7 418 |
7 627 |
||||||
Honduras |
16 626 |
17 478 |
18 596 |
18 827 |
18 949 |
19 289 |
22 552 |
24 711 |
27 071 |
29 661 |
|
India |
978 629 |
956 086 |
1 024 727 |
1 021 334 |
1 111 243 |
1 122 305 |
1 124 366 |
1 240 185 |
1 229 339 |
||
Indonesia |
300 200 |
306 100 |
325 700 |
356 600 |
358 700 |
392 875 |
438 564 |
466 709 |
512 741 |
496 479 |
586 167 |
Kenya |
41 897 |
45 023 |
46 063 |
49 177 |
49 765 |
51 511 |
53 561 |
53 757 |
55 429 |
||
Mozambique |
24 320 |
54 740 |
60 340 |
39 230 |
30 693 |
27 409 |
21 496 |
20 780 |
18 598 |
||
Nepal |
24 050 |
16 432 |
15 204 |
17 385 |
17 038 |
21 258 |
26 151 |
||||
Nigeria |
50 000 |
3 025 |
3 131 |
||||||||
Pakistan |
64 300 |
65 600 |
68 784 |
67 239 |
75 500 |
83 885 |
76 371 |
79 880 |
|||
Sri Lanka |
41 379 |
45 923 |
40 629 |
33 583 |
42 982 |
46 674 |
40 303 |
47 238 |
41 063 |
||
Yemen |
9 453 |
10 017 |
10 087 |
11 235 |
12 118 |
12 407 |
11 760 |
||||
Zimbabwe |
27 400 |
28 131 |
27 637 |
28 337 |
28 111 |
25 302 |
27 132 |
26 560 |
24 700 |
25 482 |
26 841 |
Middle-income (lower) |
|||||||||||
Algeria |
50 253 |
60 704 |
59 188 |
59 936 |
55 724 |
61 379 |
68 290 |
60 477 |
61 641 |
61 501 |
|
Armenia |
25 051 |
26 119 |
24 920 |
22 630 |
22 001 |
20 971 |
26 477 |
22 262 |
22 303 |
||
Azerbaijan |
37 347 |
38 608 |
38 773 |
37 755 |
37 138 |
||||||
Bolivia |
6 107 |
5 697 |
5 647 |
6 248 |
6 458 |
6 133 |
6 601 |
7 217 |
6 895 |
7 065 |
|
Bulgaria |
106 600 |
109 100 |
107 300 |
110 500 |
111 100 |
105 700 |
87 100 |
73 600 |
55 600 |
59 700 |
|
Cameroon |
16 972 |
14 618 |
16 658 |
14 318 |
15 565 |
12 969 |
|||||
Chile |
44 644 |
52 654 |
58 556 |
64 964 |
71 899 |
75 279 |
80 636 |
84 603 |
83 365 |
97 256 |
103 403 |
Colombia |
67 394 |
69 078 |
72 994 |
74 301 |
76 590 |
79 300 |
81 191 |
102 999 |
104 962 |
103 985 |
105 446 |
Costa Rica |
28 605 |
28 933 |
29 683 |
30 726 |
30 208 |
31 040 |
30 691 |
33 770 |
34 882 |
||
Cuba |
237 100 |
234 600 |
235 000 |
240 500 |
247 500 |
||||||
Czechoslovakia (former) |
176 000 |
177 000 |
177 000 |
177 000 |
176 000 |
168 000 |
143 000 |
||||
Ecuador |
23 210 |
24 050 |
27 708 |
27 340 |
28 197 |
27 131 |
32 752 |
36 626 |
36 358 |
36 844 |
|
Fiji |
6 172 |
6 346 |
7 489 |
7 504 |
7 087 |
6 454 |
4 817 |
4 913 |
4 889 |
5 124 |
|
Iran, Islamic Republic of |
68 801 |
72 963 |
85 450 |
71 100 |
77 800 |
67 600 |
71 087 |
72 661 |
71 769 |
||
Jamaica |
18 219 |
17 906 |
19 088 |
22 676 |
25 006 |
24 980 |
25 204 |
||||
Jordan |
5 643 |
6 001 |
6 173 |
6 418 |
7 435 |
7 819 |
9 118 |
10 296 |
10 610 |
13 206 |
|
Kyrgyzstan |
29 338 |
29 226 |
27 573 |
27 635 |
27 250 |
25 678 |
24 597 |
21 417 |
|||
Latvia |
40 360 |
40 908 |
40 439 |
38 559 |
36 492 |
35 119 |
50 478 |
36 335 |
31 506 |
||
Malaysia |
61 400 |
63 600 |
67 500 |
70 100 |
72 400 |
73 300 |
78 500 |
77 600 |
81 100 |
84 263 |
86 920 |
Mauritius |
9 517 |
9 871 |
11 098 |
11 099 |
11 088 |
11 421 |
11 433 |
11 225 |
12 475 |
||
Moldova, Republic of |
63 223 |
63 470 |
61 231 |
58 518 |
58 986 |
58 197 |
67 009 |
52 157 |
48 636 |
||
Mongolia |
15 700 |
16 200 |
17 600 |
14 000 |
15 200 |
11 975 |
11 882 |
9 249 |
9 701 |
13 620 |
|
Morocco |
22 182 |
24 302 |
20 597 |
27 350 |
26 892 |
20 617 |
27 350 |
26 980 |
28 438 |
29 316 |
|
Panama |
12 485 |
12 436 |
12 388 |
11 633 |
12 824 |
12 980 |
13 574 |
14 661 |
15 585 |
17 286 |
19 431 |
Peru |
40 151 |
41 814 |
42 164 |
45 005 |
43 607 |
43 263 |
42 557 |
43 219 |
|||
Philippines |
125 800 |
120 800 |
131 100 |
156 600 |
164 300 |
266 500 |
256 500 |
158 600 |
159 491 |
162 627 |
164 286 |
Poland |
382 000 |
386 000 |
383 000 |
387 000 |
377 000 |
366 000 |
360 000 |
349 000 |
325 000 |
||
Romania |
132 000 |
126 000 |
119 000 |
119 000 |
127 000 |
259 300 |
255 700 |
243 100 |
255 200 |
243 900 |
|
Senegal |
15 000 |
15 000 |
15 000 |
14 000 |
21 094 |
18 311 |
19 045 |
14 072 |
13 557 |
15 505 |
|
Slovenia |
19 610 |
19 379 |
24 650 |
23 600 |
24 062 |
22 490 |
21 050 |
22 383 |
|||
Syrian Arab Republic |
30 384 |
31 128 |
31 337 |
31 200 |
32 700 |
32 800 |
34 300 |
34 300 |
33 000 |
||
Thailand |
109 362 |
234 624 |
256 927 |
204 396 |
219 269 |
||||||
Tonga |
350 |
418 |
558 |
473 |
290 |
259 |
287 |
447 |
392 |
376 |
|
Turkey |
117 631 |
124 634 |
127 053 |
127 654 |
133 487 |
129 451 |
124 498 |
124 421 |
121 001 |
121 508 |
|
Middle-income (upper) |
|||||||||||
Argentina |
251 378 |
230 341 |
227 692 |
221 704 |
196 984 |
197 220 |
190 215 |
198 670 |
|||
Barbados |
1 642 |
2 260 |
2 198 |
1 922 |
1 807 |
1 596 |
1 193 |
1 120 |
1 419 |
1 431 |
1 446 |
Botswana |
3 200 |
4 200 |
3 100 |
3 500 |
4 800 |
5 200 |
5 200 |
4 900 |
5 100 |
5 200 |
|
Brazil |
733 199 |
550 886 |
548 358 |
||||||||
Greece |
48 440 |
47 400 |
48 780 |
49 110 |
50 933 |
49 618 |
47 861 |
48 925 |
48 845 |
48 765 |
48 925 |
Hungary |
170 000 |
170 000 |
176 000 |
173 000 |
173 000 |
169 000 |
164 000 |
159 000 |
134 000 |
135 030 |
136 040 |
Korea, Republic of |
153 900 |
166 600 |
174 200 |
181 100 |
174 700 |
177 700 |
176 532 |
173 729 |
175 217 |
177 444 |
177 895 |
Malta |
1 845 |
2 069 |
2 211 |
2 285 |
2 772 |
2 327 |
2 330 |
2 345 |
2 286 |
||
Mexico |
97 190 |
97 960 |
95 380 |
92 880 |
96 340 |
96 980 |
97 113 |
97 540 |
92 029 |
89 194 |
90 055 |
Oman |
228 |
288 |
344 |
81 |
110 |
60 |
467 |
193 |
800 |
370 |
|
Portugal |
67 567 |
67 800 |
65 300 |
62 741 |
62 544 |
46 336 |
46 873 |
45 544 |
42 684 |
41 436 |
40 749 |
Puerto Rico |
19 140 |
19 220 |
20 630 |
20 600 |
21 040 |
16 420 |
13 350 |
14 420 |
14 130 |
13 880 |
|
Russian Federation |
1 533 300 |
1 475 200 |
|||||||||
Slovakia |
46 460 |
41 956 |
40 937 |
40 238 |
|||||||
South Africa |
185 000 |
182 000 |
189 000 |
193 000 |
195 000 |
199 000 |
194 000 |
194 000 |
195 000 |
176 000 |
176 000 |
Suriname |
3 330 |
3 177 |
3 574 |
2 927 |
2 873 |
2 740 |
2 782 |
2 689 |
2 451 |
||
Trinidad and Tobago |
6 800 |
6 600 |
6 100 |
6 100 |
14 034 |
12 775 |
12 851 |
13 258 |
14 700 |
||
USSR (former) |
2 760 000 |
2 780 000 |
2 801 000 |
2 783 000 |
2 765 000 |
2 753 000 |
|||||
Uruguay |
36 034 |
36 280 |
35 228 |
35 500 |
48 717 |
47 883 |
46 454 |
42 867 |
39 397 |
39 560 |
39 599 |
Venezuela |
72 700 |
74 700 |
83 400 |
85 100 |
81 900 |
82 300 |
88 300 |
89 000 |
82 742 |
||
Yugoslavia |
93 300 |
||||||||||
Yugoslavia (former) |
214 000 |
221 000 |
225 000 |
228 000 |
223 000 |
||||||
Others |
|||||||||||
Croatia |
50 580 |
50 964 |
51 367 |
51 373 |
56 380 |
52 570 |
48 310 |
45 420 |
45 470 |
||
Czech Republic |
122 000 |
122 000 |
121 000 |
116 000 |
99 000 |
94 000 |
92 000 |
||||
Taiwan, China |
124 432 |
125 676 |
126 990 |
119 090 |
115 383 |
116 333 |
115 800 |
118 477 |
119 503 |
117 315 |
115 616 |
Ukraine |
684 000 |
681 000 |
683 000 |
653 000 |
618 000 |
606 000 |
586 000 |
||||
Source: UNIDO: Industrial Statistics, 1997. |
|||||||||||
Table 3.2. Employment in
beverages (ISIC 313), 1985-95
Country/territory |
1985 |
1986 |
1987 |
1988 |
1989 |
1990 |
1991 |
1992 |
1993 |
1994 |
1995 |
High-income non-OECD |
|||||||||||
Bermuda |
104 |
108 |
108 |
105 |
129 |
||||||
Cyprus |
1 774 |
1 762 |
1 799 |
1 927 |
2 036 |
1 905 |
1 938 |
1 989 |
2 039 |
2 027 |
2 006 |
Germany (former GDR) |
46 700 |
46 900 |
47 200 |
48 000 |
48 000 |
||||||
Hong Kong |
4 800 |
4 700 |
4 700 |
4 800 |
4 900 |
5 000 |
4 500 |
4 100 |
4 100 |
||
Israel |
2 500 |
2 703 |
3 100 |
3 400 |
3 100 |
3 300 |
4 200 |
4 000 |
4 500 |
4 699 |
|
Kuwait |
1 835 |
1 893 |
1 893 |
2 012 |
2 230 |
1 812 |
290 |
1 761 |
2 204 |
1 503 |
1 489 |
Qatar |
262 |
317 |
306 |
338 |
419 |
370 |
368 |
425 |
|||
Singapore |
2 273 |
2 264 |
2 258 |
2 330 |
2 406 |
2 439 |
2 440 |
2 306 |
2 190 |
2 156 |
2 156 |
High-income OECD |
|||||||||||
Australia |
18 000 |
18 000 |
18 000 |
18 000 |
18 000 |
18 000 |
18 000 |
17 000 |
|||
Austria |
13 000 |
13 100 |
13 000 |
12 800 |
12 400 |
12 700 |
13 000 |
13 000 |
12 345 |
11 947 |
11 902 |
Belgium |
14 700 |
14 100 |
13 700 |
13 300 |
13 100 |
12 800 |
12 600 |
12 300 |
|||
Canada |
31 000 |
31 000 |
31 200 |
31 000 |
27 000 |
24 000 |
22 000 |
27 000 |
27 000 |
26 000 |
26 000 |
Denmark |
9 822 |
9 112 |
8 672 |
8 100 |
7 100 |
7 015 |
6 932 |
6 832 |
|||
Finland |
5 000 |
5 100 |
4 900 |
4 800 |
4 800 |
5 500 |
5 400 |
4 900 |
4 200 |
4 200 |
4 150 |
France |
49 300 |
47 500 |
45 200 |
43 500 |
44 000 |
43 800 |
43 000 |
42 500 |
42 000 |
||
Germany |
112 000 |
96 761 |
89 430 |
||||||||
Germany (former FRG) |
91 555 |
89 558 |
87 674 |
85 713 |
84 614 |
86 510 |
90 041 |
89 212 |
|||
Iceland |
358 |
343 |
356 |
311 |
334 |
333 |
325 |
334 |
294 |
306 |
|
Ireland |
6 000 |
5 700 |
5 380 |
5 200 |
5 100 |
4 700 |
5 300 |
5 348 |
5 300 |
4 942 |
4 743 |
Italy |
43 000 |
43 000 |
44 000 |
26 504 |
25 883 |
25 238 |
24 093 |
24 179 |
24 266 |
||
Japan |
75 000 |
73 000 |
73 000 |
73 000 |
72 000 |
74 000 |
72 000 |
71 000 |
73 000 |
70 720 |
68 200 |
Luxembourg |
908 |
903 |
904 |
889 |
904 |
906 |
943 |
955 |
954 |
919 |
|
Netherlands |
12 000 |
12 000 |
11 937 |
11 563 |
11 384 |
11 229 |
11 611 |
11 403 |
11 217 |
10 897 |
10 897 |
New Zealand |
3 675 |
3 650 |
3 200 |
3 020 |
3 039 |
2 960 |
1 897 |
3 116 |
|||
Norway |
4 291 |
4 362 |
4 700 |
4 600 |
4 600 |
4 367 |
4 389 |
4 836 |
4 782 |
4 954 |
5 040 |
Spain |
54 488 |
55 373 |
54 872 |
50 764 |
52 574 |
52 464 |
47 176 |
45 508 |
45 619 |
46 053 |
45 838 |
Sweden |
4 400 |
4 600 |
5 000 |
5 100 |
5 000 |
4 800 |
4 827 |
4 575 |
4 348 |
4 141 |
|
United Kingdom |
73 000 |
74 000 |
70 000 |
72 000 |
73 000 |
69 000 |
69 000 |
65 000 |
62 870 |
60 840 |
52 930 |
United States |
171 000 |
16 000 |
152 000 |
151 000 |
143 000 |
137 000 |
137 000 |
134 000 |
136 000 |
128 000 |
127 200 |
Low-income |
|||||||||||
Bangladesh |
630 |
636 |
645 |
751 |
863 |
1 024 |
845 |
1 715 |
|||
Burundi |
872 |
898 |
835 |
776 |
722 |
654 |
|||||
Cambodia |
2 639 |
2 748 |
2 736 |
2 593 |
2 410 |
2 246 |
2 402 |
||||
Central African Republic |
331 |
287 |
244 |
232 |
214 |
278 |
265 |
235 |
|||
China |
582 000 |
613 000 |
643 000 |
677 000 |
669 000 |
1 100 000 |
1 160 000 |
1 180 000 |
1 130 000 |
1 170 000 |
|
Egypt |
21 081 |
18 497 |
21 568 |
22 102 |
19 345 |
18 300 |
12 100 |
21 300 |
21 300 |
21 135 |
|
Ethiopia and Eritrea |
7 859 |
8 261 |
8 746 |
8 863 |
9 149 |
||||||
Ghana |
4 238 |
3 792 |
5 303 |
3 418 |
3 514 |
||||||
Honduras |
4 099 |
6 416 |
6 788 |
6 911 |
7 064 |
4 265 |
4 181 |
4 336 |
4 750 |
5 205 |
|
India |
46 793 |
46 380 |
50 340 |
52 137 |
51 612 |
55 996 |
56 789 |
59 112 |
68 116 |
||
Indonesia |
11 300 |
11 700 |
11 700 |
13 000 |
12 300 |
12 550 |
16 491 |
16 738 |
21 127 |
22 168 |
23 723 |
Kenya |
6 399 |
6 328 |
5 782 |
6 505 |
6 597 |
6 733 |
6 956 |
7 029 |
7 232 |
||
Madagascar |
3 118 |
3 506 |
2 943 |
2 912 |
|||||||
Malawi |
1 876 |
1 773 |
1 304 |
1 257 |
1 812 |
||||||
Mozambique |
2 580 |
2 140 |
1 940 |
1 710 |
2 734 |
2 627 |
839 |
1 101 |
1 398 |
||
Nepal |
1 628 |
1 900 |
1 584 |
1 628 |
2 081 |
2 690 |
3 221 |
||||
Nigeria |
28 000 |
6 694 |
6 575 |
||||||||
Pakistan |
5 500 |
6 100 |
4 908 |
5 833 |
5 695 |
5 501 |
5 687 |
5 949 |
|||
Sri Lanka |
7 411 |
4 605 |
5 462 |
5 106 |
6 447 |
5 026 |
4 793 |
5 170 |
4 733 |
||
Tanzania, United Republic of |
3 706 |
3 807 |
4 107 |
4 406 |
|||||||
Uganda |
2 065 |
1 546 |
1 729 |
1 943 |
2 080 |
||||||
Yemen (northern part) |
1 656 |
1 442 |
1 010 |
||||||||
Zambia |
4 566 |
2 849 |
|||||||||
Zimbabwe |
7 100 |
7 090 |
6 928 |
7 175 |
7 468 |
6 702 |
6 747 |
6 000 |
6 900 |
6 900 |
6 899 |
Middle-income (lower) |
|||||||||||
Algeria |
13 501 |
16 309 |
15 901 |
16 102 |
14 971 |
16 490 |
18 347 |
16 248 |
16 560 |
16 523 |
|
Armenia |
7 034 |
6 473 |
6 548 |
6 064 |
5 728 |
5 038 |
|||||
Azerbaijan |
12 201 |
12 576 |
12 613 |
10 644 |
9 647 |
||||||
Bolivia |
3 545 |
3 462 |
3 379 |
3 685 |
3 568 |
3 802 |
3 800 |
4 336 |
4 257 |
4 274 |
|
Bulgaria |
20 500 |
20 300 |
20 400 |
20 500 |
21 400 |
21 600 |
16 500 |
13 700 |
12 100 |
15 000 |
|
Cameroon |
7 712 |
7 127 |
6 556 |
5 968 |
4 476 |
3 224 |
|||||
Colombia |
24 659 |
23 935 |
23 704 |
24 353 |
23 810 |
23 300 |
23 207 |
23 547 |
24 168 |
24 405 |
24 914 |
Costa Rica |
3 243 |
3 390 |
3 755 |
3 713 |
3 195 |
3 277 |
3 756 |
4 137 |
4 183 |
||
Cuba |
5 900 |
5 760 |
5 530 |
5 870 |
6 130 |
||||||
Czechoslovakia (former) |
34 000 |
34 000 |
34 000 |
34 000 |
34 000 |
34 000 |
32 000 |
||||
Ecuador |
5 222 |
5 582 |
6 400 |
6 849 |
6 472 |
7 350 |
7 887 |
7 946 |
6 402 |
7 008 |
|
Fiji |
559 |
541 |
422 |
486 |
555 |
594 |
554 |
505 |
559 |
564 |
|
Guatemala |
4 550 |
4 216 |
4 861 |
4 752 |
5 242 |
||||||
Iran, Islamic Republic of |
10 839 |
10 608 |
10 745 |
9 000 |
8 800 |
8 500 |
8 532 |
8 656 |
10 059 |
||
Iraq |
6 536 |
6 441 |
5 801 |
3 880 |
4 000 |
||||||
Jamaica |
2 414 |
2 713 |
2 990 |
3 322 |
3 295 |
3 460 |
3 492 |
||||
Jordan |
966 |
843 |
760 |
669 |
698 |
819 |
829 |
1 000 |
1 290 |
2 020 |
|
Kyrgyzstan |
2 749 |
2 838 |
2 934 |
2 896 |
2 941 |
2 865 |
2 582 |
2 284 |
|||
Latvia |
3 413 |
3 147 |
3 027 |
2 771 |
2 798 |
2 713 |
3 168 |
3 142 |
2 947 |
||
Malaysia |
5 700 |
5 400 |
5 100 |
4 800 |
4 300 |
4 500 |
4 700 |
4 400 |
4 300 |
4 418 |
4 462 |
Mauritius |
1 821 |
1 823 |
1 950 |
2 078 |
2 135 |
2 264 |
2 471 |
2 542 |
2 577 |
||
Moldova, Republic of |
12 742 |
12 850 |
11 905 |
7 791 |
12 080 |
11 579 |
13 213 |
12 699 |
10 863 |
||
Mongolia |
418 |
424 |
487 |
1 006 |
1 651 |
||||||
Morocco |
8 973 |
13 476 |
9 807 |
10 393 |
9 620 |
6 961 |
8 596 |
8 210 |
6 060 |
11 787 |
|
Panama |
1 754 |
1 895 |
2 035 |
1 846 |
1 662 |
1 599 |
1 651 |
1 650 |
1 646 |
1 643 |
1 643 |
Papua New Guinea |
1 367 |
1 550 |
1 532 |
1 519 |
1 539 |
||||||
Peru |
12 852 |
14 003 |
14 688 |
14 030 |
13 181 |
12 798 |
11 909 |
11 696 |
|||
Philippines |
27 816 |
26 650 |
27 194 |
30 200 |
31 000 |
33 200 |
33 200 |
28 100 |
28 034 |
28 310 |
28 727 |
Poland |
32 000 |
32 000 |
32 000 |
30 000 |
29 000 |
29 000 |
31 000 |
30 000 |
31 000 |
||
Romania |
50 000 |
57 000 |
61 000 |
61 000 |
65 000 |
||||||
Senegal |
545 |
524 |
493 |
418 |
381 |
359 |
|||||
Swaziland |
412 |
408 |
514 |
442 |
503 |
535 |
|||||
Thailand |
55 824 |
42 722 |
51 351 |
95 349 |
20 868 |
||||||
Tonga |
52 |
62 |
83 |
70 |
43 |
38 |
43 |
||||
Tunisia |
3 076 |
3 296 |
|||||||||
Turkey |
11 911 |
11 626 |
12 048 |
13 355 |
13 958 |
13 897 |
14 785 |
13 580 |
13 362 |
13 282 |
|
Middle-income (upper) |
|||||||||||
Argentina |
40 448 |
42 951 |
43 514 |
50 463 |
41 743 |
31 942 |
40 851 |
40 638 |
|||
Barbados |
704 |
674 |
623 |
655 |
544 |
487 |
459 |
623 |
640 |
633 |
631 |
Botswana |
400 |
600 |
800 |
900 |
1 200 |
1 300 |
1 300 |
800 |
900 |
800 |
|
Brazil |
77 167 |
84 012 |
84 941 |
||||||||
Greece |
11 380 |
10 930 |
10 370 |
10 520 |
10 668 |
10 321 |
10 050 |
9 690 |
9 731 |
9 837 |
9 900 |
Hungary |
26 000 |
26 000 |
26 000 |
25 000 |
25 000 |
25 000 |
23 000 |
20 000 |
18 000 |
18 190 |
18 380 |
Korea, Republic of |
26 100 |
26 100 |
29 100 |
28 500 |
26 200 |
24 000 |
18 694 |
17 628 |
17 292 |
17 375 |
17 357 |
Malta |
1 156 |
1 151 |
1 250 |
1 262 |
1 205 |
1 219 |
1 229 |
1 271 |
1 261 |
||
Mexico |
76 080 |
79 620 |
78 100 |
76 480 |
80 790 |
84 980 |
86 707 |
88 096 |
87 176 |
87 015 |
87 842 |
Portugal |
8 375 |
8 300 |
8 328 |
8 536 |
8 723 |
11 824 |
11 821 |
10 529 |
10 561 |
10 847 |
10 749 |
Puerto Rico |
4 060 |
4 220 |
2 870 |
3 030 |
3 130 |
1 520 |
1 500 |
1 550 |
1 580 |
1 650 |
|
Russian Federation |
141 300 |
143 500 |
|||||||||
Slovakia |
9 284 |
9 107 |
8 843 |
9 106 |
|||||||
South Africa |
35 000 |
35 000 |
36 000 |
37 000 |
39 000 |
36 000 |
36 000 |
37 000 |
35 000 |
33 000 |
33 520 |
Suriname |
527 |
573 |
441 |
581 |
575 |
589 |
433 |
609 |
652 |
||
Trinidad and Tobago |
1 900 |
1 700 |
1 700 |
1 700 |
1 382 |
1 623 |
1 342 |
1 683 |
1 500 |
||
USSR (former) |
369 000 |
333 000 |
310 000 |
301 000 |
294 000 |
300 000 |
|||||
Uruguay |
5 404 |
5 627 |
5 660 |
4 900 |
5 926 |
5 609 |
5 242 |
4 998 |
5 071 |
5 071 |
4 444 |
Venezuela |
14 500 |
14 000 |
14 100 |
15 500 |
16 000 |
16 000 |
16 000 |
17 000 |
16 916 |
||
Yugoslavia (former) |
39 000 |
43 000 |
42 000 |
44 000 |
42 000 |
||||||
Others |
|||||||||||
Croatia |
9 172 |
8 859 |
9 079 |
8 833 |
9 140 |
8 130 |
7 770 |
7 630 |
7 490 |
||
Czech Republic |
24 000 |
24 000 |
24 000 |
24 000 |
22 000 |
22 000 |
23 000 |
||||
The former Yugoslav Republic of Macedonia |
3 044 |
3 020 |
3 151 |
4 692 |
2 218 |
1 978 |
1 894 |
2 895 |
|||
Taiwan, China |
11 558 |
11 759 |
12 253 |
13 118 |
14 386 |
15 730 |
15 442 |
15 619 |
15 712 |
15 510 |
15 285 |
Ukraine |
64 000 |
65 000 |
67 000 |
66 000 |
64 000 |
63 000 |
61 000 |
||||
Source: UNIDO: Industrial Statistics, 1997. |
|||||||||||
Table 3.3. Employment in food products
as a percentage of employment in total manufacturing, 1985-95
Country/territory |
1985 |
1986 |
1987 |
1988 |
1989 |
1990 |
1991 |
1992 |
1993 |
1994 |
1995 |
High-income non-OECD |
|||||||||||
Bermuda |
19.60 |
18.81 |
17.29 |
16.25 |
16.03 |
||||||
Cyprus |
12.10 |
12.92 |
12.88 |
13.03 |
13.37 |
13.57 |
13.62 |
13.80 |
14.49 |
16.15 |
16.37 |
Germany (former GDR) |
7.17 |
7.14 |
7.17 |
7.21 |
7.26 |
||||||
Hong Kong |
2.04 |
2.00 |
2.08 |
2.18 |
2.25 |
2.75 |
3.27 |
3.51 |
4.04 |
||
Israel |
14.27 |
14.89 |
16.03 |
16.58 |
15.05 |
14.38 |
14.29 |
13.76 |
13.77 |
13.94 |
|
Kuwait |
13.81 |
14.49 |
12.73 |
12.40 |
12.52 |
13.84 |
12.36 |
10.96 |
11.44 |
11.56 |
11.57 |
Qatar |
9.19 |
9.24 |
9.62 |
9.58 |
9.25 |
8.11 |
8.31 |
8.00 |
|||
Singapore |
3.81 |
3.89 |
3.68 |
3.20 |
3.08 |
3.02 |
3.10 |
3.23 |
3.34 |
3.23 |
3.12 |
High-income OECD |
|||||||||||
Australia |
14.17 |
14.20 |
14.24 |
14.30 |
14.42 |
14.75 |
15.34 |
16.07 |
|||
Austria |
8.14 |
8.07 |
8.27 |
8.31 |
8.10 |
8.22 |
8.15 |
8.51 |
8.92 |
8.85 |
8.92 |
Belgium |
9.84 |
9.90 |
10.12 |
10.38 |
10.37 |
10.33 |
10.54 |
10.69 |
|||
Canada |
10.78 |
10.81 |
10.59 |
10.33 |
10.23 |
10.60 |
11.05 |
11.64 |
11.48 |
11.32 |
11.11 |
Denmark |
16.39 |
16.39 |
16.59 |
16.48 |
16.16 |
17.11 |
17.22 |
17.21 |
|||
Finland |
10.32 |
10.62 |
10.78 |
10.92 |
10.59 |
10.79 |
11.12 |
11.40 |
11.28 |
10.53 |
10.43 |
France |
10.16 |
10.37 |
10.65 |
10.81 |
10.75 |
10.63 |
10.71 |
10.93 |
11.26 |
||
Germany |
5.78 |
6.23 |
6.57 |
||||||||
Germany (former FRG) |
5.07 |
4.97 |
5.01 |
5.04 |
5.12 |
5.28 |
5.57 |
5.69 |
|||
Iceland |
44.92 |
45.64 |
45.89 |
44.41 |
50.60 |
49.81 |
49.20 |
48.71 |
50.45 |
52.30 |
|
Ireland |
20.87 |
20.63 |
20.41 |
20.22 |
19.31 |
18.94 |
19.28 |
18.52 |
18.20 |
17.38 |
16.20 |
Italy |
5.39 |
5.11 |
5.19 |
5.89 |
5.64 |
5.90 |
5.98 |
5.98 |
6.04 |
||
Japan |
9.67 |
9.99 |
10.22 |
10.24 |
10.22 |
10.19 |
10.16 |
10.44 |
10.89 |
10.64 |
10.69 |
Luxembourg |
6.02 |
6.05 |
6.25 |
6.40 |
6.76 |
6.89 |
7.52 |
7.86 |
8.70 |
8.41 |
|
Netherlands |
14.18 |
14.02 |
14.28 |
14.09 |
13.87 |
13.81 |
14.07 |
14.18 |
14.97 |
15.02 |
15.20 |
New Zealand |
24.10 |
24.11 |
23.51 |
25.79 |
25.25 |
26.65 |
27.88 |
27.86 |
27.21 |
||
Norway |
15.13 |
15.12 |
15.13 |
15.67 |
16.25 |
16.20 |
16.43 |
16.30 |
16.36 |
16.43 |
16.43 |
Spain |
12.73 |
12.77 |
12.93 |
13.74 |
13.55 |
13.56 |
13.94 |
14.49 |
14.69 |
14.67 |
14.74 |
Sweden |
8.10 |
8.24 |
8.18 |
8.35 |
8.48 |
8.55 |
8.76 |
8.93 |
9.67 |
9.17 |
|
Switzerland |
8.26 |
8.29 |
8.36 |
8.35 |
8.40 |
8.49 |
8.65 |
8.83 |
9.03 |
||
United Kingdom |
9.87 |
9.97 |
10.34 |
10.20 |
10.31 |
10.48 |
10.92 |
11.17 |
11.14 |
10.83 |
10.72 |
United States |
7.17 |
7.33 |
7.37 |
7.37 |
7.42 |
7.62 |
8.01 |
8.11 |
8.21 |
8.14 |
8.09 |
Low-income |
|||||||||||
Bangladesh |
9.75 |
9.84 |
10.13 |
10.45 |
12.70 |
10.77 |
9.38 |
9.18 |
|||
Burundi |
12.63 |
19.99 |
19.19 |
18.34 |
21.52 |
24.10 |
|||||
Cambodia |
13.84 |
13.13 |
12.53 |
12.61 |
10.60 |
10.46 |
14.62 |
||||
Central African Republic |
8.47 |
10.08 |
10.01 |
9.81 |
9.83 |
10.30 |
11.65 |
10.64 |
|||
China |
7.80 |
7.99 |
8.08 |
8.27 |
8.14 |
5.75 |
5.90 |
5.93 |
5.98 |
5.85 |
|
Egypt |
16.34 |
16.56 |
17.78 |
17.24 |
17.98 |
18.97 |
21.59 |
17.84 |
19.14 |
19.54 |
|
Ethiopia and Eritrea |
19.61 |
20.05 |
19.00 |
18.54 |
18.31 |
||||||
Ghana |
11.89 |
12.35 |
14.69 |
9.43 |
9.43 |
||||||
Haiti |
21.94 |
21.90 |
24.04 |
24.38 |
|||||||
Honduras |
25.97 |
26.27 |
27.16 |
27.27 |
26.95 |
24.53 |
23.35 |
22.09 |
22.38 |
22.38 |
|
India |
14.88 |
14.65 |
15.02 |
14.92 |
15.38 |
15.38 |
15.28 |
15.81 |
15.56 |
||
Indonesia |
17.95 |
18.23 |
18.33 |
17.33 |
15.96 |
14.83 |
14.71 |
14.15 |
14.41 |
13.07 |
13.87 |
Kenya |
25.74 |
26.81 |
26.78 |
27.29 |
27.56 |
27.45 |
28.36 |
28.25 |
28.64 |
||
Lesotho |
20.20 |
16.19 |
13.21 |
12.13 |
11.09 |
||||||
Madagascar |
37.25 |
30.57 |
35.78 |
35.78 |
|||||||
Malawi |
34.83 |
42.97 |
42.27 |
||||||||
Mozambique |
38.92 |
49.04 |
51.87 |
47.21 |
40.19 |
38.76 |
40.85 |
40.96 |
40.37 |
||
Nepal |
17.58 |
11.74 |
10.87 |
12.81 |
10.88 |
9.96 |
12.00 |
||||
Nicaragua |
35.81 |
||||||||||
Nigeria |
15.26 |
11.16 |
11.65 |
||||||||
Pakistan |
13.04 |
12.95 |
12.97 |
13.06 |
13.34 |
13.48 |
13.17 |
13.17 |
|||
Sri Lanka |
19.60 |
21.15 |
19.14 |
15.32 |
17.64 |
16.51 |
14.02 |
16.47 |
12.52 |
||
Tanzania, United Republic of |
18.82 |
25.23 |
26.89 |
28.49 |
|||||||
Uganda |
26.44 |
9.03 |
12.34 |
17.68 |
48.22 |
||||||
Yemen |
38.40 |
39.34 |
39.01 |
41.87 |
42.64 |
40.95 |
43.78 |
||||
Zambia |
27.51 |
24.85 |
|||||||||
Zimbabwe |
16.76 |
16.74 |
16.11 |
15.52 |
15.15 |
13.73 |
14.43 |
12.05 |
14.30 |
14.17 |
15.36 |
Middle-income (lower) |
|||||||||||
Albania |
12.50 |
13.80 |
13.56 |
24.38 |
|||||||
Algeria |
11.97 |
13.58 |
13.67 |
13.77 |
12.67 |
14.11 |
15.16 |
14.18 |
14.49 |
14.49 |
|
Armenia |
6.07 |
6.25 |
6.08 |
6.05 |
6.21 |
6.48 |
8.60 |
7.91 |
7.93 |
||
Azerbaijan |
10.42 |
11.19 |
12.35 |
13.24 |
13.62 |
||||||
Bolivia |
21.91 |
21.67 |
22.46 |
23.68 |
23.46 |
21.85 |
22.62 |
22.63 |
20.65 |
20.47 |
|
Bulgaria |
8.10 |
8.22 |
8.16 |
8.25 |
7.57 |
7.69 |
7.84 |
7.86 |
6.79 |
8.58 |
|
Cameroon |
24.11 |
28.95 |
26.34 |
24.16 |
28.14 |
26.17 |
|||||
Chile |
24.13 |
25.53 |
25.30 |
25.01 |
24.66 |
25.25 |
26.23 |
25.90 |
25.00 |
28.29 |
29.22 |
Colombia |
15.32 |
15.35 |
15.54 |
15.63 |
15.79 |
16.22 |
16.58 |
17.74 |
17.81 |
17.63 |
17.96 |
Congo |
37.11 |
42.84 |
45.74 |
44.80 |
|||||||
Costa Rica |
27.53 |
26.88 |
25.44 |
25.70 |
22.94 |
23.10 |
22.81 |
23.07 |
22.96 |
||
Cuba |
36.23 |
35.39 |
35.41 |
35.48 |
35.37 |
||||||
Czechoslovakia (former) |
6.80 |
6.81 |
6.82 |
6.83 |
6.84 |
6.86 |
7.31 |
||||
Ecuador |
23.97 |
23.65 |
25.63 |
25.05 |
25.64 |
24.29 |
26.34 |
29.14 |
29.88 |
29.80 |
|
El Salvador |
16.53 |
19.66 |
16.36 |
18.26 |
|||||||
Fiji |
46.61 |
47.83 |
55.19 |
49.44 |
37.57 |
31.12 |
25.04 |
28.25 |
26.38 |
27.04 |
|
Guatemala |
33.07 |
32.80 |
30.19 |
26.91 |
35.00 |
||||||
Iran, Islamic Republic of |
11.31 |
12.35 |
12.61 |
11.27 |
11.81 |
10.36 |
11.39 |
11.33 |
11.59 |
||
Jamaica |
35.50 |
33.48 |
33.87 |
36.48 |
38.49 |
38.83 |
38.50 |
||||
Jordan |
13.47 |
14.03 |
13.96 |
14.37 |
17.06 |
17.65 |
17.78 |
16.00 |
15.73 |
16.22 |
|
Kyrgyzstan |
11.17 |
11.16 |
9.62 |
9.72 |
10.03 |
10.70 |
11.43 |
12.98 |
|||
Latvia |
9.86 |
10.04 |
10.30 |
10.29 |
10.56 |
10.68 |
18.04 |
18.54 |
19.23 |
||
Malaysia |
12.97 |
13.37 |
13.11 |
11.77 |
10.50 |
8.82 |
8.13 |
7.59 |
7.11 |
6.71 |
6.33 |
Mauritius |
12.76 |
10.66 |
10.37 |
9.83 |
9.65 |
9.95 |
9.70 |
10.00 |
10.86 |
||
Moldova, Republic of |
16.09 |
16.11 |
15.80 |
15.27 |
15.82 |
17.68 |
20.92 |
24.74 |
37.68 |
||
Mongolia |
2.07 |
2.13 |
2.32 |
1.84 |
2.00 |
21.11 |
21.33 |
22.60 |
26.26 |
28.48 |
|
Morocco |
8.18 |
8.18 |
6.40 |
7.70 |
6.57 |
4.98 |
6.42 |
6.17 |
6.40 |
6.58 |
|
Panama |
34.57 |
34.23 |
33.88 |
36.18 |
40.85 |
35.22 |
35.86 |
36.51 |
37.34 |
39.96 |
44.92 |
Papua New Guinea |
35.74 |
36.18 |
33.03 |
34.98 |
34.98 |
||||||
Peru |
15.25 |
14.99 |
13.89 |
14.41 |
14.96 |
15.16 |
16.71 |
18.20 |
|||
Philippines |
20.34 |
19.17 |
19.54 |
18.53 |
17.47 |
24.04 |
23.20 |
16.54 |
16.43 |
16.48 |
16.30 |
Poland |
10.68 |
10.82 |
10.86 |
11.18 |
11.33 |
12.14 |
13.48 |
15.03 |
15.00 |
||
Romania |
4.33 |
4.08 |
3.87 |
3.88 |
4.06 |
7.51 |
7.96 |
8.65 |
9.85 |
10.06 |
|
Senegal |
50.00 |
55.56 |
56.00 |
58.75 |
56.38 |
63.06 |
55.86 |
58.33 |
55.27 |
||
Slovenia |
5.20 |
5.20 |
6.49 |
6.62 |
7.26 |
7.41 |
7.52 |
8.44 |
|||
Swaziland |
48.72 |
49.85 |
43.11 |
38.90 |
50.28 |
48.01 |
|||||
Syrian Arab Republic |
29.32 |
30.14 |
31.24 |
30.65 |
31.47 |
32.60 |
33.37 |
33.42 |
32.74 |
||
Thailand |
12.05 |
22.86 |
18.76 |
11.78 |
13.73 |
||||||
Tonga |
35.79 |
35.27 |
35.95 |
33.74 |
27.00 |
23.35 |
28.82 |
36.64 |
40.08 |
43.12 |
|
Turkey |
13.94 |
14.23 |
13.93 |
13.39 |
13.82 |
13.26 |
13.82 |
13.74 |
13.28 |
13.68 |
|
Middle-income (upper) |
|||||||||||
Argentina |
21.40 |
21.27 |
21.25 |
20.54 |
19.77 |
20.94 |
22.14 |
22.39 |
|||
Barbados |
18.18 |
22.91 |
22.53 |
19.95 |
24.08 |
23.74 |
19.72 |
19.45 |
24.99 |
28.49 |
29.55 |
Botswana |
32.00 |
34.43 |
21.09 |
21.34 |
21.15 |
21.40 |
20.16 |
22.48 |
24.52 |
23.53 |
|
Brazil |
13.33 |
13.16 |
15.00 |
||||||||
Greece |
13.75 |
13.75 |
13.97 |
14.02 |
14.52 |
14.33 |
14.64 |
15.41 |
15.54 |
15.68 |
15.83 |
Hungary |
13.30 |
13.40 |
14.16 |
14.32 |
14.77 |
15.13 |
16.30 |
18.49 |
17.94 |
17.39 |
17.24 |
Korea, Republic of |
6.42 |
6.19 |
5.90 |
5.91 |
5.76 |
6.01 |
6.26 |
6.35 |
6.25 |
6.23 |
6.00 |
Malta |
7.23 |
7.84 |
8.02 |
8.39 |
9.80 |
8.69 |
8.74 |
8.84 |
8.72 |
||
Mexico |
9.78 |
9.96 |
10.07 |
9.82 |
9.96 |
10.01 |
10.16 |
10.64 |
10.82 |
11.02 |
11.85 |
Oman |
9.98 |
8.34 |
22.15 |
8.18 |
6.41 |
1.88 |
15.87 |
9.61 |
36.99 |
29.86 |
|
Portugal |
10.87 |
10.89 |
10.51 |
10.23 |
10.25 |
9.48 |
9.93 |
10.03 |
9.87 |
9.99 |
9.83 |
Puerto Rico |
12.86 |
12.61 |
13.83 |
13.12 |
13.24 |
12.71 |
10.86 |
11.60 |
11.47 |
11.40 |
|
Russian Federation |
9.36 |
10.05 |
|||||||||
Slovakia |
7.75 |
8.03 |
8.72 |
9.01 |
|||||||
South Africa |
13.01 |
12.87 |
12.77 |
12.61 |
12.74 |
13.05 |
13.07 |
13.46 |
13.90 |
12.58 |
12.29 |
Suriname |
44.88 |
44.21 |
49.99 |
43.08 |
41.43 |
43.62 |
43.32 |
41.36 |
41.96 |
||
Trinidad and Tobago |
20.29 |
20.98 |
19.98 |
20.12 |
40.14 |
33.69 |
36.41 |
35.16 |
38.08 |
||
USSR (former) |
8.42 |
8.47 |
8.55 |
8.68 |
8.86 |
9.07 |
|||||
Uruguay |
29.55 |
28.73 |
27.03 |
28.00 |
28.28 |
28.53 |
29.09 |
29.08 |
29.33 |
28.82 |
28.85 |
Venezuela |
17.92 |
17.91 |
17.79 |
17.22 |
17.51 |
17.72 |
17.75 |
17.99 |
18.05 |
||
Yugoslavia (former) |
8.67 |
8.58 |
8.60 |
8.67 |
8.39 |
||||||
Others |
|||||||||||
Croatia |
9.01 |
9.04 |
9.12 |
9.27 |
10.32 |
11.72 |
12.40 |
12.26 |
12.85 |
||
Czech Republic |
7.30 |
7.33 |
7.32 |
7.36 |
7.12 |
7.30 |
7.65 |
||||
The former Yugoslav Republic of Macedonia |
7.49 |
7.40 |
5.63 |
6.79 |
8.28 |
8.72 |
9.22 |
9.19 |
|||
Taiwan, China |
5.05 |
4.88 |
4.83 |
4.61 |
4.70 |
5.14 |
5.28 |
5.43 |
5.51 |
5.41 |
5.41 |
Ukraine |
13.15 |
13.32 |
13.80 |
13.47 |
12.91 |
12.45 |
13.36 |
||||
Source: UNIDO: Industrial Statistics, 1997. |
|||||||||||
Table 3.4. Employment in
beverages as a percentage of employment in total manufacturing, 1985-95
Country/territory |
1985 |
1986 |
1987 |
1988 |
1989 |
1990 |
1991 |
1992 |
1993 |
1994 |
1995 |
High-income non-OECD |
|||||||||||
Bermuda |
9.39 |
9.91 |
10.04 |
10.10 |
11.75 |
||||||
Cyprus |
4.58 |
4.67 |
4.58 |
4.64 |
4.79 |
4.40 |
4.53 |
4.58 |
4.97 |
5.12 |
5.02 |
Germany (former GDR) |
1.56 |
1.58 |
1.59 |
1.62 |
1.64 |
||||||
Hong Kong |
0.53 |
0.50 |
0.50 |
0.54 |
0.59 |
0.66 |
0.69 |
0.69 |
0.81 |
||
Israel |
0.86 |
0.92 |
1.02 |
1.16 |
1.05 |
1.13 |
1.38 |
1.27 |
1.37 |
1.34 |
|
Kuwait |
4.03 |
4.23 |
3.51 |
3.46 |
3.95 |
3.25 |
0.75 |
3.24 |
3.74 |
2.57 |
2.57 |
Qatar |
1.58 |
1.89 |
1.89 |
1.97 |
2.30 |
1.50 |
1.57 |
1.70 |
|||
Singapore |
0.89 |
0.92 |
0.82 |
0.72 |
0.71 |
0.69 |
0.68 |
0.64 |
0.62 |
0.59 |
0.57 |
High-income OECD |
|||||||||||
Australia |
1.77 |
1.78 |
1.77 |
1.71 |
1.70 |
1.77 |
1.87 |
1.87 |
|||
Austria |
1.99 |
2.04 |
2.07 |
2.06 |
1.96 |
1.98 |
2.08 |
2.17 |
2.20 |
2.16 |
2.17 |
Belgium |
1.96 |
1.90 |
1.90 |
1.85 |
1.79 |
1.74 |
1.75 |
1.75 |
|||
Canada |
1.76 |
1.72 |
1.68 |
1.59 |
1.37 |
1.29 |
1.27 |
1.61 |
1.64 |
1.56 |
1.53 |
Denmark |
2.43 |
2.21 |
2.15 |
2.07 |
1.82 |
1.37 |
1.40 |
1.41 |
|||
Finland |
1.01 |
1.07 |
1.05 |
1.06 |
1.08 |
1.27 |
1.34 |
1.35 |
1.23 |
1.22 |
1.21 |
France |
1.09 |
1.06 |
1.04 |
1.02 |
1.02 |
1.01 |
1.00 |
1.02 |
1.05 |
||
Germany |
1.27 |
1.34 |
1.33 |
||||||||
Germany (former FRG) |
1.38 |
1.33 |
1.30 |
1.27 |
1.22 |
1.22 |
1.25 |
1.26 |
|||
Iceland |
1.20 |
1.14 |
1.14 |
1.10 |
1.42 |
1.48 |
1.47 |
1.63 |
1.49 |
1.54 |
|
Ireland |
3.22 |
3.09 |
2.94 |
2.82 |
2.69 |
2.43 |
2.72 |
2.73 |
2.72 |
2.48 |
2.31 |
Italy |
1.50 |
1.51 |
1.53 |
0.96 |
0.93 |
0.92 |
0.88 |
0.89 |
0.90 |
||
Japan |
0.70 |
0.68 |
0.69 |
0.68 |
0.67 |
0.66 |
0.63 |
0.64 |
0.67 |
0.66 |
0.64 |
Luxembourg |
2.48 |
2.43 |
2.47 |
2.50 |
2.51 |
2.53 |
2.60 |
2.68 |
2.79 |
2.69 |
|
Netherlands |
1.51 |
1.49 |
1.47 |
1.53 |
1.48 |
1.44 |
1.48 |
1.47 |
1.56 |
1.53 |
1.53 |
New Zealand |
1.32 |
1.32 |
1.25 |
1.30 |
1.29 |
1.40 |
0.94 |
1.51 |
|||
Norway |
1.37 |
1.38 |
1.50 |
1.57 |
1.67 |
1.61 |
1.66 |
1.97 |
1.95 |
1.99 |
2.01 |
Spain |
3.04 |
3.13 |
3.05 |
2.76 |
2.79 |
2.75 |
2.49 |
2.50 |
2.53 |
2.54 |
2.55 |
Sweden |
0.57 |
0.60 |
0.65 |
0.67 |
0.67 |
0.67 |
0.67 |
0.69 |
0.75 |
0.70 |
|
United Kingdom |
1.48 |
1.51 |
1.45 |
1.47 |
1.49 |
1.44 |
1.54 |
1.51 |
1.46 |
1.38 |
1.20 |
United States |
0.98 |
0.95 |
0.86 |
0.85 |
0.81 |
0.78 |
0.82 |
0.79 |
0.81 |
0.75 |
0.74 |
Low-income |
|||||||||||
Bangladesh |
0.13 |
0.14 |
0.13 |
0.15 |
0.09 |
0.10 |
0.08 |
0.15 |
|||
Burundi |
17.46 |
16.81 |
15.00 |
13.33 |
11.01 |
9.73 |
|||||
Cambodia |
2.85 |
2.99 |
2.91 |
3.02 |
2.94 |
2.67 |
3.13 |
||||
Central African Republic |
4.23 |
5.02 |
5.01 |
4.90 |
4.92 |
5.13 |
5.80 |
5.30 |
|||
China |
1.96 |
1.98 |
2.00 |
2.03 |
2.00 |
2.07 |
2.13 |
2.14 |
2.16 |
2.15 |
|
Egypt |
2.32 |
2.03 |
2.21 |
2.17 |
1.84 |
1.70 |
1.08 |
1.97 |
1.94 |
1.91 |
|
Ethiopia and Eritrea |
8.93 |
9.09 |
9.20 |
8.98 |
9.09 |
||||||
Ghana |
6.91 |
6.16 |
6.35 |
4.35 |
4.35 |
||||||
Haiti |
4.73 |
3.65 |
4.20 |
4.37 |
|||||||
Honduras |
6.40 |
9.64 |
9.91 |
10.01 |
10.05 |
5.42 |
4.33 |
3.88 |
3.93 |
3.93 |
|
India |
0.71 |
0.71 |
0.74 |
0.76 |
0.71 |
0.77 |
0.77 |
0.75 |
0.86 |
||
Indonesia |
0.68 |
0.70 |
0.66 |
0.63 |
0.55 |
0.47 |
0.55 |
0.51 |
0.59 |
0.58 |
0.56 |
Kenya |
3.93 |
3.77 |
3.36 |
3.61 |
3.65 |
3.59 |
3.68 |
3.69 |
3.74 |
||
Madagascar |
6.64 |
8.41 |
7.13 |
7.13 |
|||||||
Malawi |
6.11 |
7.47 |
5.85 |
||||||||
Mozambique |
4.13 |
1.92 |
1.67 |
2.06 |
3.58 |
3.71 |
1.59 |
2.17 |
3.03 |
||
Nepal |
1.19 |
1.36 |
1.13 |
1.20 |
1.33 |
1.26 |
1.48 |
||||
Nigeria |
8.54 |
24.70 |
24.46 |
||||||||
Pakistan |
1.12 |
1.20 |
0.93 |
1.13 |
1.01 |
0.88 |
0.98 |
0.98 |
|||
Sri Lanka |
3.51 |
2.12 |
2.57 |
2.33 |
2.65 |
1.78 |
1.67 |
1.80 |
1.44 |
||
Tanzania, United Republic of |
3.95 |
3.47 |
3.68 |
3.88 |
|||||||
Uganda |
9.25 |
9.91 |
9.99 |
10.07 |
3.68 |
||||||
Zambia |
6.75 |
5.59 |
|||||||||
Zimbabwe |
4.34 |
4.22 |
4.04 |
3.93 |
4.02 |
3.64 |
3.59 |
2.72 |
4.00 |
3.84 |
3.95 |
Middle-income (lower) |
|||||||||||
Algeria |
3.22 |
3.65 |
3.67 |
3.70 |
3.40 |
3.79 |
4.07 |
3.81 |
3.89 |
3.89 |
|
Armenia |
1.70 |
1.55 |
1.60 |
1.62 |
1.62 |
1.56 |
|||||
Azerbaijan |
3.40 |
3.64 |
4.02 |
3.73 |
3.54 |
||||||
Belize |
6.02 |
5.80 |
|||||||||
Bolivia |
12.72 |
13.17 |
13.44 |
13.97 |
12.96 |
13.54 |
13.02 |
13.60 |
12.75 |
12.38 |
|
Bulgaria |
1.56 |
1.53 |
1.55 |
1.53 |
1.46 |
1.57 |
1.49 |
1.46 |
1.48 |
2.16 |
|
Cameroon |
10.96 |
14.12 |
10.37 |
10.07 |
8.09 |
6.50 |
|||||
Chile |
3.88 |
3.45 |
3.53 |
3.59 |
3.65 |
3.43 |
3.62 |
3.56 |
3.52 |
3.36 |
3.40 |
Colombia |
5.61 |
5.32 |
5.05 |
5.12 |
4.91 |
4.77 |
4.74 |
4.05 |
4.10 |
4.14 |
4.24 |
Congo |
13.50 |
15.57 |
16.64 |
16.30 |
|||||||
Costa Rica |
3.12 |
3.15 |
3.22 |
3.11 |
2.43 |
2.44 |
2.79 |
2.83 |
2.75 |
||
Cuba |
0.90 |
0.87 |
0.83 |
0.87 |
0.88 |
||||||
Czechoslovakia (former) |
1.31 |
1.31 |
1.31 |
1.31 |
1.32 |
1.39 |
1.64 |
||||
Ecuador |
5.39 |
5.49 |
5.92 |
6.28 |
5.89 |
6.58 |
6.34 |
6.32 |
5.26 |
5.67 |
|
Fiji |
4.22 |
4.08 |
3.11 |
3.20 |
2.94 |
2.86 |
2.88 |
2.90 |
3.02 |
2.98 |
|
Guatemala |
6.23 |
6.09 |
7.54 |
5.12 |
8.25 |
||||||
Iran, Islamic Republic of |
1.78 |
1.80 |
1.59 |
1.43 |
1.34 |
1.30 |
1.37 |
1.35 |
1.62 |
||
Iraq |
3.75 |
3.62 |
4.20 |
3.09 |
3.18 |
||||||
Jamaica |
4.70 |
5.07 |
5.31 |
5.34 |
5.07 |
5.38 |
5.33 |
||||
Jordan |
2.31 |
1.97 |
1.72 |
1.50 |
1.60 |
1.85 |
1.62 |
1.55 |
1.91 |
2.48 |
|
Kyrgyzstan |
1.05 |
1.08 |
1.02 |
1.02 |
1.08 |
1.19 |
1.20 |
1.38 |
|||
Latvia |
0.83 |
0.77 |
0.77 |
0.74 |
0.81 |
0.82 |
1.13 |
1.60 |
1.80 |
||
Malaysia |
1.20 |
1.13 |
0.99 |
0.81 |
0.62 |
0.54 |
0.49 |
0.43 |
0.38 |
0.35 |
0.32 |
Mauritius |
2.44 |
1.97 |
1.82 |
1.84 |
1.86 |
1.97 |
2.10 |
2.26 |
2.24 |
||
Moldova, Republic of |
3.24 |
3.26 |
3.07 |
2.03 |
3.24 |
3.52 |
4.13 |
6.02 |
8.42 |
||
Mongolia |
0.74 |
0.76 |
1.19 |
2.72 |
3.45 |
||||||
Morocco |
3.31 |
4.54 |
3.05 |
2.93 |
2.35 |
1.68 |
2.02 |
1.88 |
1.36 |
2.65 |
|
Panama |
4.86 |
5.22 |
5.57 |
5.74 |
5.29 |
4.34 |
4.36 |
4.11 |
3.94 |
3.80 |
3.80 |
Papua New Guinea |
6.34 |
7.04 |
6.92 |
6.77 |
6.77 |
||||||
Peru |
4.88 |
5.02 |
4.84 |
4.49 |
4.52 |
4.49 |
4.68 |
4.92 |
|||
Philippines |
4.50 |
4.23 |
4.05 |
3.57 |
3.30 |
3.00 |
3.00 |
2.93 |
2.89 |
2.87 |
2.85 |
Poland |
0.89 |
0.90 |
0.91 |
0.87 |
0.87 |
0.96 |
1.16 |
1.29 |
1.43 |
||
Romania |
1.64 |
1.85 |
1.98 |
1.99 |
2.08 |
||||||
Senegal |
1.52 |
1.61 |
1.63 |
1.66 |
1.64 |
1.28 |
|||||
Slovenia |
1.15 |
1.12 |
|||||||||
Swaziland |
3.53 |
3.45 |
3.90 |
3.08 |
2.80 |
2.67 |
|||||
Thailand |
6.15 |
4.16 |
3.75 |
5.49 |
1.31 |
||||||
Tonga |
5.32 |
5.23 |
5.35 |
4.99 |
4.00 |
3.43 |
4.32 |
||||
Turkey |
1.41 |
1.33 |
1.32 |
1.40 |
1.45 |
1.42 |
1.64 |
1.50 |
1.47 |
1.50 |
|
Middle-income (upper) |
|||||||||||
Argentina |
3.44 |
3.97 |
4.06 |
4.68 |
4.19 |
3.39 |
4.76 |
4.58 |
|||
Barbados |
7.79 |
6.83 |
6.39 |
6.80 |
7.25 |
7.24 |
7.59 |
10.82 |
11.27 |
12.60 |
12.90 |
Botswana |
4.00 |
4.92 |
5.44 |
5.49 |
5.29 |
5.35 |
5.04 |
3.67 |
4.33 |
3.62 |
|
Brazil |
1.40 |
2.01 |
2.32 |
||||||||
Greece |
3.23 |
3.17 |
2.97 |
3.00 |
3.04 |
2.98 |
3.07 |
3.05 |
3.10 |
3.16 |
3.20 |
Hungary |
2.03 |
2.05 |
2.09 |
2.07 |
2.13 |
2.24 |
2.29 |
2.33 |
2.41 |
2.34 |
2.33 |
Korea, Republic of |
1.09 |
0.97 |
0.99 |
0.93 |
0.86 |
0.81 |
0.66 |
0.64 |
0.62 |
0.61 |
0.59 |
Malta |
4.53 |
4.36 |
4.53 |
4.63 |
4.26 |
4.55 |
4.61 |
4.79 |
4.81 |
||
Mexico |
7.65 |
8.10 |
8.25 |
8.09 |
8.35 |
8.77 |
9.07 |
9.61 |
10.25 |
10.75 |
11.56 |
Portugal |
1.35 |
1.33 |
1.34 |
1.39 |
1.43 |
2.42 |
2.50 |
2.32 |
2.44 |
2.62 |
2.59 |
Puerto Rico |
2.73 |
2.77 |
1.92 |
1.93 |
1.97 |
1.18 |
1.22 |
1.25 |
1.28 |
1.36 |
|
Russian Federation |
0.86 |
0.98 |
|||||||||
Slovakia |
1.55 |
1.74 |
1.88 |
2.04 |
|||||||
South Africa |
2.46 |
2.48 |
2.43 |
2.42 |
2.55 |
2.36 |
2.43 |
2.57 |
2.49 |
2.36 |
2.34 |
Suriname |
7.10 |
7.97 |
6.17 |
8.55 |
8.29 |
9.38 |
6.74 |
9.37 |
11.16 |
||
Trinidad and Tobago |
5.67 |
5.40 |
5.57 |
5.61 |
3.95 |
4.28 |
3.80 |
4.46 |
3.89 |
||
USSR (former) |
1.13 |
1.01 |
0.95 |
0.94 |
0.94 |
0.99 |
|||||
Uruguay |
4.43 |
4.46 |
4.34 |
3.86 |
3.44 |
3.34 |
3.28 |
3.39 |
3.78 |
3.69 |
3.24 |
Venezuela |
3.57 |
3.36 |
3.01 |
3.14 |
3.42 |
3.45 |
3.22 |
3.44 |
3.69 |
||
Yugoslavia (former) |
1.58 |
1.67 |
1.61 |
1.67 |
1.58 |
||||||
Others |
|||||||||||
Croatia |
1.63 |
1.57 |
1.61 |
1.59 |
1.67 |
1.81 |
2.00 |
2.06 |
2.12 |
||
Czech Republic |
1.44 |
1.44 |
1.45 |
1.52 |
1.58 |
1.71 |
1.91 |
||||
The former Yugoslav Republic of Macedonia |
1.60 |
1.59 |
1.69 |
2.53 |
1.25 |
1.17 |
1.23 |
1.99 |
|||
Taiwan, China |
0.47 |
0.46 |
0.47 |
0.51 |
0.59 |
0.69 |
0.70 |
0.72 |
0.72 |
0.72 |
0.72 |
Ukraine |
1.23 |
1.27 |
1.35 |
1.36 |
1.34 |
1.29 |
1.39 |
||||
Source: UNIDO: Industrial Statistics, 1997. |
|||||||||||
In comparison with the food industry, the proportion of workers in the drink industry within total manufacturing declined in a larger number of high-income countries, suggesting that labour-saving capital investments in this industry are more than keeping pace with other manufacturing sectors. In middle-income and lower-income countries the picture is mixed, with the proportion rising in some and falling in others.
The four tables presented above show that the employment decline in the food and drink industries has been most striking in the industrialized countries of Europe. Table 3.5 gives the level of total employment as at 1995 for a number of branches of the FD industries in the EU and the percentage change since 1988. It shows that employment declined in most branches, with the beer and sugar refinery sectors experiencing the sharpest decline. The other branches to experience a relatively large loss include oils and fats, spirits, grain milling and pasta. Available information indicates that these branches have been the target of heavy investments in recent years in order to enhance productivity. In this sense, the employment decline in the FD industries in the EU as presented in the table is closely associated with the adoption of new technology.
Table 3.5. European Union:
Employment in the FD branches in 1995 and changes since 1988
Branches |
Employment |
% change 1988-95 |
Bakery products |
455 611 |
6.4 |
Meat products |
434 280 |
1.9 |
Dairy products |
248 343 |
-2.4 |
Chocolate/confectionery |
162 806 |
1.9 |
Fruit/vegetable processing |
131 113 |
1.4 |
Beer |
116 483 |
-18.7 |
Non-alcoholic drinks |
87 958 |
-7.7 |
Animal feed |
87 226 |
-2.9 |
Fish processing |
79 860 |
-4.6 |
Sugar refineries |
57 471 |
-18.9 |
Wine |
48 112 |
-0.8 |
Oils and fats |
47 652 |
-12.2 |
Spirits |
41 721 |
-15.7 |
Grain milling |
35 251 |
-11.6 |
Pasta |
19 031 |
-15.7 |
Other products |
198 288 |
13.6 |
Total food, drink, tobacco |
2 311 343 |
-8.6 |
Source: European Commission: Panorama of EU Industry, 1997, Vol. 1 (Brussels, 1997). |
||
National information sources often contain more detailed, reliable or recent statistics than those given in tables 3.1 and 3.2. For Belgium,(3) employment in the food industry declined by 2.2 per cent for the period 1991-95, falling from 78,047 to 76,364 workers. The branches that produce oils and fats, dairy, sugar and pasta products saw a greater percentage decline than some other branches of the food industry. For example, employment in the oils and fats branch declined by 24.4 per cent between 1992 and 1995, while employment in the drink industry decreased by 15.4 per cent for the same period, from 12,559 to 10,633. Employment in the distillery branch plunged by 81.4 per cent, while in the brewery branch it shrank by 16.5 per cent during the same period. While the entire decline in employment may not be the result of investments in new technology, there does seem to be some correlation. In the brewery branch, for example, employment declined rapidly while investment in this branch climbed continuously between 1990 and 1992. The level of investment in the distillery branch increased up to 1995, and in the oils and fats branch it increased threefold from 1989 to 1990.
The employment trend index in the FD industries in Germany for the period 1985-95 is presented in table 3.6. It shows a consistent decline in employment in the drinks industry, similar to that seen in other industrialized countries.
Table 3.6. Germany: Employment1
trends in the food and drink industries, 1985-95 (1993 = 100)
Area |
Sector |
1985 |
1988 |
1993 |
1994 |
1995 |
Former FRG |
Food |
82 |
86 |
100 |
99 |
97 |
Sweets/pastries |
89 |
92 |
100 |
97 |
94 |
|
Meat |
89 |
92 |
100 |
99 |
97 |
|
Drink |
103 |
97 |
100 |
94 |
90 |
|
Former GDR |
Food |
- |
- |
100 |
101 |
102 |
Sweets/pastries |
- |
- |
100 |
98 |
94 |
|
Meat |
- |
- |
100 |
99 |
97 |
|
Drink |
- |
- |
100 |
91 |
86 |
|
1 Including all employees covered by social
security. |
||||||
As regards the share of German FD industries in total manufacturing employment, the proportion increased gradually from 6.2 per cent in 1988 to 7.1 per cent in 1993 in the former FRG, while it rose from 7.9 per cent in 1991 to 10.3 per cent in 1993 in the former GDR. The proportion grew from 6.9 per cent in 1991 to 7.4 per cent in Germany as a whole.(4) This suggests that FD employment is faring better than that in other manufacturing sectors.
The number of FD workers in Portugal has also been declining. The introduction of new technology is believed to be partly responsible for this trend. The other element that has been singled out is the fact that an increasing number of small enterprises are being driven to closure by dominant retailers who have moved into the country. Their negotiating power is said to allow small firms little room for manoeuvre. In spite of the declining trend in employment in the FD industries, there have been some branches, such as meat, where it has increased; in this case the installation of new technology, and the consequent need to recover the investment, is judged to have had a positive effect on production, sales and employment.(5)
Table 3.7 presents the employment levels in selected branches of the food sector in the United Kingdom in 1980 and 1992 and the percentage change during that period. Although the slaughter industry has suffered from excess capacity for many years, employment in the meat products branch as a whole in 1992 was much higher than in 1980. This was mainly due to increased demand for poultry in general and for poultry and pork-based ready meal products of higher value, the production of which is labour-intensive. The slower than average decline in employment in the bakery and confectionery branch has been partly attributed to an increase in small specialist establishments making cakes and pastries. The branches that experienced a large fall in employment, such as sugar, oils and fats and grain milling, are involved mainly in first-stage processing, the standardized products of which offer more scope for automation. In addition to the introduction of labour-saving technology, a study undertaken by the NEDC indicated that slow market growth, in segments such as milk processing and bakery, was another reason for the decline in employment in those branches.(6) A number of cases illustrate the impact of new technology on employment at plant level in the United Kingdom. For example, the total number of production and laboratory staff at a brewery located in Park Royal, London dropped from 476 in 1991 to 243 in 1997 following investments of approximately £100 million since 1992 on new plants equipped with new technology. At a confectionery plant located in Oxfordshire, the number of workers -- including production and office staff -- was halved from 1,600 in 1989 to 815 in 1997 as a direct result of major investments of over £50 million since 1995.(7)
Table 3.7. United Kingdom:
Employment in the food industry, 1980 and 1992 (Census of production groups:
SIC 1980)
Group (1980) |
Industry |
Employment |
Change (%) |
|
|
|
|
||
1980 |
1992 |
|||
411 |
Organic oils and fats |
8 836 |
5 197 |
-41.2 |
412 |
Slaughtering and meat products |
96 237 |
117 031 |
21.6 |
413 |
Milk and milk products |
52 088 |
39 045 |
-25.0 |
414 |
Fruit and vegetable processing |
26 755 |
20 297 |
-24.1 |
415 |
Fish processing |
28 453 |
19 700 |
-30.8 |
416 |
Grain milling |
8 957 |
5 941 |
-33.7 |
419 |
Bread, biscuits and flour confectionery |
161 248 |
151 365 |
-6.1 |
420 |
Sugar and sugar by-products |
11 463 |
5 208 |
-54.6 |
421 |
Ice-cream, cocoa, chocolate and sugar confectionery |
67 632 |
50 727 |
-25.0 |
422 |
Animal feeds |
27 967 |
20 090 |
-28.2 |
418/423 |
Starch and miscellaneous foods |
66 217 |
61 312 |
-7.4 |
Source: J.A. Burns with Marian Garcia: The impact of technical change on employment in the UK food and drink industries, project for the ILO (University of Reading, July 1997), p. 28. |
||||
Prior to the economic transition, the food industry in Hungary employed more than 200,000 workers, or around 4 per cent of the total national labour force; this figure then fell to 127,000 by 1996, or 3.5 per cent of the total labour force. The major reason for this decline was the privatization of approximately 80 per cent of the industry, which led to the elimination of inefficient production and overcapacity and the rationalization of production through restructuring and the adoption of new technology. A number of firms were driven to bankruptcy in the process, thus contributing to the employment decline seen in this industry.(8) Table 3.8 presents employment trends in various branches of the FD industries in Hungary for the period 1992-95. It shows that total employment in the FD industries was reduced by 29 per cent during the period. The branches with a significant percentage loss include meat and meat processing (-35 per cent, fruit and vegetable products (-25 per cent), fodder (-60 per cent), bakery (-30 per cent), sugar (-33 per cent), chocolate and confectionery (-37 per cent), pastry (-45 per cent), alcohol and alcohol beverages (-36 per cent), wine (-35 per cent) and beer (-40 per cent). The decline in these branches is due in part to reduced demand and also to the deterioration in the agricultural raw material supply that affected output in meat and fruit and vegetable processing. The introduction of new technology in privatized firms to achieve higher productivity also played a part in the employment decline.(9) As table 1.18 in Chapter 1 shows, the sectors showing a sharp decrease in employment (meat, fruit and vegetable, confectionery and brewery branches) received a considerable share of the total investment in the FD industries between 1990 and 1995. Although the actual amount of investment in fodder had not been significant until 1995, it more than doubled between 1994 and 1995.
Table 3.8. Employment in
Hungarian food and drink industries, 1992-95 (thousands)
Branch |
1992 |
1993 |
1994 |
1995 |
Meat and meat processing |
36.6 |
30.3 |
29.3 |
23.8 |
Poultry |
14.5 |
12.8 |
11.6 |
13.5 |
Fruit and vegetable products |
22.0 |
16.4 |
17.2 |
16.6 |
Dairy |
17.7 |
17.2 |
16.3 |
15.3 |
Milling |
4.2 |
6.7 |
6.9 |
6.8 |
Fodder |
18.6 |
11.3 |
7.7 |
7.3 |
Bakery |
24.0 |
20.7 |
18.1 |
16.9 |
Sugar |
6.7 |
5.4 |
4.9 |
4.5 |
Chocolate and confectionery |
6.3 |
5.1 |
4.1 |
4.0 |
Pastry |
0.9 |
0.8 |
0.6 |
0.5 |
Alcohol and alcoholic beverages |
3.6 |
3.0 |
2.6 |
2.3 |
Wine |
5.1 |
4.3 |
3.7 |
3.3 |
Beer |
8.1 |
7.5 |
6.4 |
4.8 |
Non-alcoholic beverages |
3.7 |
3.3 |
3.3 |
3.7 |
Food products and beverages |
180.2 |
151.6 |
139.0 |
128.3 |
Tobacco |
3.4 |
3.0 |
2.7 |
2.5 |
Food, beverages and tobacco products |
183.6 |
154.6 |
141.7 |
130.8 |
Source: Judit Kiss: Technology and employment in the Hungarian food and drink industry (Budapest, Institute for World Economics of the Hungarian Academy of Sciences, Mar. 1997), unpublished paper, p. 26. |
||||
Employment in the food industry in Japan expanded from 1,030,000 jobs in 1985 to 1,185,000 in 1993, after which it declined to 1,145,000 by 1995, as shown in table 3.1. On the other hand, employment in the drink industry has been on a downward trend ever since 1985, as indicated in table 3.2, and by 1995 the workforce had shrunk by 9 per cent. The rise in the number of workers in the food industry was largely due to the increased utilization of part-time and non-regular workers.(10) To take an example, the results of an employment status survey(11) conducted in 1987 and 1992 show that total employment in the FDT industries increased from 1,247,000 to 1,427,000, of which the proportion of non-regular workers, including part-time workers, increased from 430,000 (34.5 per cent of the total) to 493,000 (35.6 per cent). More recent data indicate that the proportion of part-time workers among the total workforce employed in food, drink, animal feed and tobacco manufacturing firms employing more than five workers increased from 23.9 per cent in 1992 to 26.9 per cent in 1996.(12) Many cases of employment decline have been reported in Japanese firms where new technology has been introduced in recent years. A large dairy processing firm, for example, has invested heavily in computerizing various activities in recent years, including production, marketing and distribution, and the total number of regular employees declined from 7,224 in 1990 to 6,764 in 1996. On the other hand, the workforce expanded in some firms. For example, a large frozen food manufacturer increased the number of its regular employees from 1,897 in 1990 to 2,366 in 1995, though this figure fell to 2,168 by 1996.(13) The employment increase at this particular firm, despite the adoption of new information technology, was largely due to the growing demand for frozen foods.
Although employment in the food industry in the United States continued to increase until 1993 (see table 3.1), the impact of new technology on employment has been felt in certain branches and in a number of plants in other parts of North America. A confectionery firm in Canada, for example, reported a 35 per cent decline in the workforce since 1990, despite an increase in production as a result of new technology.(14) Nabisco's Richmond plant has lost over 100 employees since 1994, when approximately 900 people were employed, owing to new technology and organizational changes.(15) Table 3.9 presents employment trends in the FDT industries in the United States for the period 1991-95. Although employment in the FD industries as a whole (indicated in the table as food and kindred products) rose from 1991 to 1993 and then declined in 1995, it fell gradually in most of the branches shown. The meat products branch was the only branch with a continuous rise in employment, largely due to increased demand for poultry products. The table indicates that the proportion of production workers within the total workforce in the FD industries is increasing both as a whole and also in most of the branches presented. This corresponds to the fact that high technology adopted in many companies has brought about new forms of work organization where production workers' duties and responsibilities have been redefined, while many middle-management and clerical posts have been eliminated.
Table 3.9. United States:
Total employment and the proportion of production workers in the food, beverages
and tobacco industries, by subsector, 1991-95
Subsector |
19911 |
19931 |
19951 |
|||
Employees |
Production |
Employees |
Production |
Employees |
Production |
|
Food and kindred products |
1 681.6 |
72.5 |
1 684.1 |
73.4 |
1 682.4 |
74.0 |
Meat products |
435.4 |
85.2 |
448.3 |
85.3 |
473.9 |
85.4 |
Dairy products |
154.5 |
61.7 |
152.5 |
63.1 |
147.0 |
64.6 |
Preserved fruits and vegetables |
241.1 |
83.6 |
237.7 |
82.9 |
229.9 |
83.1 |
Grain mill products |
130.4 |
70.5 |
128.6 |
72.2 |
128.5 |
71.1 |
Bakery products |
216.6 |
63.8 |
214.9 |
65.4 |
211.2 |
67.7 |
Sugar/confectionery products |
111.7 |
79.6 |
115.6 |
79.8 |
111.7 |
80.1 |
Fats and oils |
31.9 |
69.3 |
31.6 |
68.7 |
31.2 |
68.3 |
Beverages |
181.4 |
42.9 |
177.7 |
46.0 |
174.5 |
46.8 |
Tobacco products |
49.8 |
74.5 |
43.6 |
76.6 |
42.4 |
76.4 |
1Data relate to November. |
||||||
The situation is similar in the FD industries in Latin America, particularly in large firms. To take an example, a brewery plant in Argentina which has invested $300 million in upgrading technology in recent years has cut the number of its employees by 2,000 to 5,500 since the mid-1980s.(16) A sugar manufacturer in Mexico cut its operative staff by 40 per cent between 1993 and 1995, and expected to reduce it by another 16 per cent in 1997. Low value-added non-production jobs were mainly affected during the massive lay-offs in 1993-95 because of the company's need to slim down after a period of state management, during which the workforce had grown out of proportion. However, more recent redundancies are more closely associated with the introduction of computer-controlled machinery and instruments.(17)
Table 3.10 gives employment trends by branch in the FD industries in India for the period 1974-93. Except for a downturn in 1988-89, total employment in these industries increased steadily during the two decades, expanding by 63 per cent since 1973-74 and by 25 per cent since 1984-85. There was a tendency for the share of total FD employment to decline in those branches in which there were high levels of investment to modernize facilities and increase capacity. For example, the proportion of employment in the fruit and vegetable processing, grain milling, bakery, hydrogenated oils and fats and soft drinks branches declined in the early 1990s. The decline in some branches might have been due to a cyclical slowdown in demand, but it appears to correspond to the level of investment, particularly in the cases of grain milling, bakery, hydrogenated oils and fats and soft drinks (see table 1.19 above).
Table 3.10. India: Employment
in the food and drink industries by branch (percentage)
Branch |
1974-75 |
1979-80 |
1984-85 |
1988-89 |
1992-93 |
Meat |
0.02 |
0.67 |
0.48 |
0.51 |
0.54 |
Dairy |
6.38 |
6.87 |
9.56 |
9.52 |
9.79 |
Fruit and vegetable |
1.23 |
2.40 |
2.01 |
2.35 |
2.21 |
Fish |
1.19 |
2.03 |
2.01 |
1.92 |
2.66 |
Grain milling |
25.85 |
29.17 |
37.66 |
39.02 |
31.94 |
Bakery |
3.96 |
4.49 |
4.86 |
5.89 |
4.79 |
Cocoa and confectionery |
0.86 |
0.61 |
0.92 |
1.07 |
1.36 |
Oils and fats (hydrogenated) |
3.53 |
3.54 |
3.58 |
3.48 |
3.14 |
Other oils and fats |
14.98 |
13.11 |
8.83 |
10.04 |
12.64 |
Coffee |
32.22 |
26.24 |
19.04 |
14.21 |
21.75 |
Ice |
0.54 |
1.03 |
0.96 |
1.50 |
1.95 |
Animal feed |
1.69 |
1.77 |
1.52 |
1.61 |
1.46 |
Other food |
5.67 |
6.27 |
6.50 |
6.14 |
3.82 |
Soft drinks and syrup |
1.50 |
1.80 |
2.07 |
2.68 |
1.95 |
Total |
100.00 |
100.00 |
100.00 |
100.00 |
100.00 |
(427 144) |
(521 253) |
(557 660) |
(555 470) |
(694 320) |
|
Note: Figures in brackets
indicate total number of workers. |
|||||
The upward trend for the total workforce in the FD industries, such as that seen in India, can be observed in a number of developing countries whose economies are experiencing strong and steady growth. On the other hand, there are many developing countries where industries, including the FD sectors, are stagnant or on a downward trend for a variety of reasons. Table 3.11 presents the employment trends in the FD companies whose employers are affiliated with the Association of Food, Beverage and Tobacco Employers (AFBTE) in Nigeria for the period 1992-96. Employment in the food sector grew by 5.7 per cent between 1992 and 1994, but has since declined by 17 per cent in spite of an increase in the number of establishments. On the other hand, employment in the drink sector continued its decline, the workforce having been cut by 42 per cent during the period shown. The employment decline was mainly due to the closure of several firms and the downsizing of others against the backdrop of a harsh economic environment. The Nigerian FD manufacturers are also faced with a serious problem of low capacity utilization. For example, the average capacity utilization in the FDT industries deteriorated from 43 per cent in 1992 to 25.5 per cent in 1995. Although it improved to 31.8 per cent by 1996, it was still far below the level considered reasonable.(18)
Table 3.11. Nigeria: Employment
and number of establishments in the food and drink industries, 1992-96
Sector |
1992 |
1993 |
1994 |
1995 |
1996 |
|
Food |
Workers |
15 208 |
15 595 |
16 072 |
14 464 |
13 294 |
Establishments |
42 |
40 |
39 |
44 |
45 |
|
Drink |
Workers |
25 428 |
24 716 |
22 362 |
21 244 |
14 633 |
Establishments |
25 |
28 |
27 |
25 |
19 |
|
Source: Association of Food, Beverage and Tobacco Employers (AFBTE): 18th Annual Publication (Lagos, Nigeria, 1996), p. 13. |
||||||
A study on the fruit processing sector in Kenya, covering enterprises of all sizes, also encountered a similar problem of low capacity utilization. The rate in this particular sector ranged from a low of 20 per cent in the canned juice and fruit preserves branches to a high of 50 per cent in the dried fruits and other branches. The reasons behind low capacity utilization included raw material shortages, low competitiveness in the face of the liberalization of imports, frequent breakdown of equipment and bureaucratic/legal impediments.(19)
Employment in the FD industries or in certain branches within the FD industries in a number of the countries reviewed above has shown a clear downward trend. While this is not attributable to any single factor, there is substantial evidence that the introduction of new labour-saving technology was closely associated with this phenomenon. Other factors behind declining employment included heightened competition due to trade liberalization and privatization, and low levels of demand.
On the other hand, employment in the FD industries is growing in some dynamic economies. In India alone, for example, some 5 million new jobs are expected to be generated all along the food chain by 2005.(20)
Changes in labour productivity
In the majority of cases, investments in new technology at the plant level have brought about faster line speed, less labour-intensiveness and increased production. There have been a few cases, however, where productivity was not particularly affected or where it even declined despite the introduction of new technology. One such case was reported in a brewery where increased production was held back by the packaging operation,(21) the level of technology of which did not match that of the production department. Since most firms are not financially capable of modernizing all their operations at once, technological mismatches of this kind may arise. In general, however, recent investment in new technology appears to be contributing to improved productivity in the FD industries.
The turnover in the FD industries in Australia increased from A$32.1 billion in 1989-90 to A$35.6 billion in 1992-93. The workforce in these industries declined from 166,357 to 153,364 during the same period. In contrast to the FD industries, the turnover in total manufacturing increased from A$167.8 billion to A$170.2 billion, while employment declined from 1,031,100 to 866,900 during the same period.(22) Simple calculations of these figures indicate that per capita turnover increased from A$192,900 to A$232,100 in the FD industries, while that in total manufacturing rose from A$162,700 to A$196,300 during the same period. Although per capita turnover grew slightly faster in total manufacturing (20.7 per cent ) than in the FD industries (20.3 per cent), the productivity in the latter remained much higher than in the former.
Table 3.12 presents the per capita productivity index for non-skilled and skilled workers in the food industry and total manufacturing in Germany for the period 1988-93. The annual productivity growth rate was higher in the food industry than in total manufacturing. A comparison of skilled and non-skilled workers shows that the latter achieved higher productivity than skilled workers in both total manufacturing and the food industry. This was probably due to the fact that the new technology introduced had been targeted more at increasing production line efficiency than at the areas where white-collar workers are assigned.
Table 3.12. Germany: Per
capita productivity index in the food industry and total manufacturing, by category
of workers, 1988-93 (1985 = 100)
Year |
Total manufacturing |
Food industry |
||
Non-skilled |
Skilled |
Non-skilled |
Skilled |
|
1988 |
107.0 |
105.5 |
107.0 |
107.1 |
1989 |
110.5 |
108.8 |
110.4 |
110.7 |
1990 |
113.7 |
111.8 |
118.9 |
120.3 |
1991 |
116.4 |
113.8 |
118.2 |
120.8 |
1992 |
118.0 |
113.7 |
119.4 |
120.9 |
1993 |
120.1 |
113.2 |
125.0 |
124.5 |
Average annual growth rate 1988-93 |
2.3 |
1.4 |
3.2 |
3.1 |
Source: Michael Breitenacher and Uwe Christian Täger: Branchenuntersuchung Ernährungsindustrie, ifo Struktur und Wachstum, Industrial Series, Issue No. 48 (Germany). |
||||
The productivity index for various branches of the FD industries in Hungary for 1994-95 is shown in table 3.13. In comparison to 1993, productivity growth for the FD industries was higher in 1994 than in 1995. While productivity in each and every branch was better in 1994 than in 1993, it declined in three branches in 1995. The rise in poultry, milling, chocolate/confectionery, pastry, beer and non-alcoholic beverages in 1994 was particularly remarkable, and this was likely to have been closely related to the level of investment in these branches, which jumped significantly from the previous year in all but pastry (see table 1.18). The level of investment in 1995 resulted in higher productivity compared to the previous year in most branches, with the exception of poultry and bakery. In some branches, however, productivity rose despite falling investment (e.g. pastry and other food products).
Table 3.13. Hungary: Productivity
index in the food and drink industries, by branch, 1994-95
Subsector |
Gross output per employee (previous year = 100) |
|
1994 |
1995 |
|
Meat and meat products |
103.1 |
121.3 |
Poultry |
136.3 |
99.6 |
Fruit and vegetable products |
115.2 |
110.1 |
Vegetable oil |
n.a. |
n.a. |
Dairy |
102.0 |
104.1 |
Milling |
192.1 |
128.2 |
Fodder |
114.6 |
106.1 |
Bakery |
104.2 |
99.5 |
Sugar |
104.9 |
125.7 |
Chocolate and confectionery |
123.5 |
115.1 |
Pastry |
189.9 |
146.7 |
Other food products |
118.4 |
112.4 |
Alcohol and alcoholic beverages |
115.1 |
65.1 |
Wine |
109.9 |
128.6 |
Beer |
126.1 |
131.6 |
Non-alcoholic beverages |
136.2 |
115.3 |
Food products and beverages |
115.0 |
111.6 |
Tobacco |
121.9 |
98.0 |
Food products, beverages and tobacco products |
115.2 |
111.1 |
Source: Judit Kiss: Technology and employment in the Hungarian food and drink industry (Budapest, Institute for World Economics of the Hungarian Academy of Sciences, Mar. 1997), unpublished paper, p. 22. |
||
The productivity of the FD industries in Hungary was also higher than the all-industry average. To take an example, the FD industries produced 23.3 and 21.6 per cent of the total gross industrial output in 1994 and 1995, respectively, while they employed 17.4 and 16.8 per cent of the total industrial labour force for the respective years. The increase in the gross output of the FD industries of 5.5 and 2.4 per cent in 1994 and 1995 respectively and the decline in the labour force by 8.4 and 7.8 per cent respectively were largely attributed to technological change, investments and recent restructuring.(23)
In India a case-study on a large bakery undertaking in the public sector that has diversified into several other FD subsectors shows that the value added per employee in this company jumped from Rs.19,246 in 1994 to Rs.64,860 in 1997. Since the late 1980s, this company has invested heavily in time-saving machinery of superior quality in mixing, fermentation, slicing and packaging systems, some of which has been imported from the United States. It plans to invest an additional Rs.1 to 1.5 billion to further upgrade its facilities by automating its production. It also increased its R & D expenditure from Rs.1.3 million in 1994-95, or 0.11 per cent of turnover, to Rs.2.5 million in 1995-96, or 0.18 per cent of turnover, with the aim of developing new products and improving the quality of existing ones.(24)
The index (1990=100) of the average labour productivity of the FD industries in Japan gradually declined in the 1990s and totalled 84.7 in 1996 as opposed to 108.5 for total manufacturing. Labour input in the FD industries increased, mostly in the form of part-time and non-regular employment in smaller enterprises which opted for cheaper labour rather than investing in costly new technology. This was compounded by the impact of a prolonged recession, reduced demand and increased trade liberalization in the 1990s. However, not all companies were necessarily affected in the same way, particularly the larger ones. For example, labour productivity increased by 17 per cent from 1994 to 1996 at a large confectionery firm. A major brewery improved its productivity by 30 per cent during the same period, while another leading firm with diversified activities experienced a 5 per cent gain. In all these companies, the employment level declined slightly, falling, for example, from 5,308 to 5,265 at the confectionery firm.(25)
Table 3.14 presents fixed assets and added value per employee in the food industry and in total manufacturing in Malaysia. Fixed assets in the food industry were higher than those in total manufacturing in 1985, but grew much more slowly and were overtaken by those in total manufacturing. This reflects the recent economic trend in Malaysia where the development of heavy industries is being vigorously promoted. Despite a rapid increase in fixed assets in total manufacturing, the added value per employee grew faster in the food industry than in total manufacturing. In fact, the added value in the food industry was still 14 per cent higher than in total manufacturing in 1992.
Table 3.14. Malaysia:
Fixed assets and added value per employee in the food industry and manufacturing,
1985-92 (M$ in current prices)
Year |
Fixed assets per employee (excl. land/building) |
Added value per employee |
||
Food |
Manufacturing |
Food |
Manufacturing |
|
1985 |
24 492 |
19 146 |
20 487 |
18 500 |
1987 |
23 277 |
19 099 |
18 781 |
19 439 |
1989 |
21 865 |
17 872 |
28 006 |
23 148 |
1991 |
23 561 |
23 155 |
24 051 |
25 021 |
1992 |
25 841 |
28 032 |
31 413 |
27 544 |
Average annual |
0.77 |
5.60 |
6.30 |
5.85 |
Source: National Productivity Corporation: Productivity Report 1994 (Petaling Jaya, Malaysia, 1995). |
||||
A study published in 1994 by McKinsey Global Institute on Latin American productivity covered food processing, among other industries. It found that labour productivity in food processing in Argentina, Brazil, Colombia, Mexico and Venezuela averaged between 30 to 50 per cent of the level in the United States and that the low productivity in the region was mainly due to organizational inefficiency. It further pointed out that productivity in food processing had not improved much, despite the fact that the industry had been privately owned and highly fragmented. It claimed that a history of food price controls and high tariffs on machinery imports, among other factors, had discouraged investment, resulting in low productivity. However, it also showed that the productivity gap with the United States had narrowed in Brazil, Colombia and Mexico between 1987 and 1992, though only by a few percentage points at most.(26) Productivity in the United States food-processing industry was rising during that period.
Although productivity in Mexico's FD industries rose by 3.3 per cent between 1990 and 1996, the rate of increase was lower than the all-industry average of 6 per cent. In one sugar refinery, the daily processing capacity was reported to have increased from 3,000 to 4,000 tonnes per day during the period 1992-96. This was believed to be the result of approximately $7 million investment in new PLC-controlled systems in the milling, centrifuge, vats and evaporation areas during that period.(27)
According to the Ministry of Agriculture and Fisheries in New Zealand, labour productivity in the dairy industry increased by 7.4 per cent per annum for the period 1990-95. This was greater than an estimated all-industry annual rate of increase of 4 per cent for the same period. The productivity rise in the dairy industry is believed to be largely associated with heavy investments made in the sector since 1990.(28)
Labour productivity in the food industry in Turkey increased by 10 per cent between 1986 and 1990. However, it was reported that this was one of the sectors which exhibited slow growth rates in 1996. Therefore, the food industry in both the public and private sectors is being urged to place greater emphasis on productivity improvement to ensure its competitiveness vis-à-vis European Union countries.(29)
Table 3.15 presents the index numbers representing the changing levels of output, employment and productivity in total manufacturing and in the FDT industries in the United Kingdom for the period 1989-96. The output in the FDT industries grew slightly more than in total manufacturing, while the employment decline was greater in total manufacturing than in the FDT industries. Consequently, productivity in the FDT industries grew more slowly than in total manufacturing.
When productivity in terms of gross value added per head in the FD industries is compared to that in the tobacco industry in the United Kingdom (see table 1.20), it is both much lower and has a slower rate of growth. By way of example, productivity in the tobacco industry was 1.8 times greater than in the FD industries in 1986, and this difference widened to more than five times as much by 1993. This is mainly due to the fact that productivity gains from additional capital investments were greater in the tobacco industry. For this reason, productivity growth for the FD industries, excluding the tobacco industry, should be much lower than the figure indicated for the FDT industries in table 3.15. Nevertheless, according to table 1.20 productivity in terms of gross value added per head grew by nearly 50 per cent between 1986 and 1993.
Table 3.15. United Kingdom:
Production, employment and output per worker in total manufacturing and in the
food, drink and tobacco industries, 1989-96
1989 |
1990 |
1991 |
1992 |
1993 |
1994 |
1995 |
1996 |
|
Total manufacturing output |
100.2 |
100.0 |
94.6 |
94.0 |
95.3 |
99.3 |
101.5 |
102.0 |
FDT output |
98.6 |
100.0 |
98.7 |
100.0 |
100.1 |
102.0 |
104.0 |
104.5 |
Total manufacturing employment |
102.7 |
100.0 |
92.3 |
86.8 |
83.8 |
83.4 |
84.1 |
84.2 |
FDT employment |
100.9 |
100.0 |
98.9 |
94.8 |
92.5 |
89.7 |
89.5 |
90.9 |
Total per capita manufacturing output |
97.8 |
100.0 |
102.5 |
108.4 |
113.7 |
119.1 |
120.7 |
121.1 |
FDT per capita output |
97.7 |
100.0 |
99.8 |
105.4 |
108.3 |
113.8 |
116.3 |
115.1 |
Source: J.A. Burns with Marian Garcia: The impact of technical change on employment in the UK food and drink industries, project for the ILO (University of Reading, July 1997), p. 24. |
||||||||
The indexes of output per hour in total manufacturing and selected FD branches as well as in the tobacco industry in the United States for the period 1988-95 are given in table 3.16. Productivity in many branches as well as in total manufacturing dropped in the late 1980s, later recovered and grew. As in the United Kingdom, the tobacco industry achieved a high growth rate, although growth in the soft drinks branch was even greater. Many branches of the FD industries shown here achieved a higher productivity rate than total manufacturing.
Table 3.16. United States:
Index numbers of hourly output, by sector, 1988-95 (1987 = 100)
Sector |
1988 |
1990 |
1992 |
1994 |
1995 |
Total manufacturing |
90.9 |
94.2 |
102.1 |
108.9 |
113.1 |
Meat packing plants |
100.9 |
96.8 |
104.5 |
101.0 |
101.7 |
Poultry dressing/processing |
96.2 |
108.6 |
119.6 |
119.4 |
122.5 |
Cheese, natural/processed |
99.8 |
108.2 |
121.8 |
117.5 |
120.5 |
Canned fruits/vegetables |
98.7 |
93.8 |
101.5 |
101.5 |
109.3 |
Frozen fruits/vegetables |
94.0 |
90.0 |
96.4 |
109.3 |
111.1 |
Cereal breakfast foods |
98.6 |
100.2 |
99.1 |
106.6 |
118.4 |
Beet sugar |
97.6 |
97.6 |
110.8 |
124.2 |
135.9 |
Malt beverages |
99.1 |
110.6 |
113.4 |
117.5 |
118.0 |
Soft drinks |
109.8 |
126.7 |
144.2 |
150.4 |
160.0 |
Tobacco |
104.8 |
109.9 |
113.4 |
130.1 |
149.2 |
Source: US Department of Labor: Monthly Labor Review (Washington, DC, June 1997), Vol. 120, No. 6, p. 95. |
|||||
As examined above, labour productivity in the FD industries in many countries has risen in recent years. Some branches improved their performance remarkably, while others achieved moderate growth. Even in some countries where the productivity of the FD industries as a whole declined, certain firms managed to increase their output per employee. Information from a variety of sources underlined the key role played by labour-saving technology in stabilizing or increasing output with a smaller or equal-sized workforce.
Employment flexibility and women workers
The introduction of new technology in combination with intensified global competition in the FD industries has brought about growing flexibility in employment and working conditions. Firms are increasingly redeploying their workforce to perform different or more varied tasks (functional flexibility) in different locations (site flexibility). They are also adjusting labour input to product demand through numerical flexibility, for example, by greater recourse to non-regular workers who can be terminated more easily and/or with fewer social obligations when they are no longer needed.
Women are particularly affected by this trend. The jobs that are most likely to disappear because of new technology are those that are simple, manual and repetitive. Because female workers in general have had less training and are therefore less skilled than their male counterparts and because they have largely held repetitive jobs, their positions are increasingly being replaced by computer-controlled machines. Women also account for a large share of the non-regular workers whose relative numbers are increasing. The following paragraphs illustrate how these trends are developing in selected countries and enterprises.
The study on management strategy undertaken in March 1996 by the Japan Food Industry Centre Institute listed the reduction of labour costs and the active utilization of part-time workers as priority measures for food manufacturing firms to cope better with the current harsh market situation. The share of part-time workers in the total workforce in the food industry in Japan is reported to be around 30 per cent, and though this has not changed much for several years, it is still considerably higher than in other sectors. For example, part-time workers account for about 11 per cent of the manufacturing workforce as a whole and 28 per cent of the workforce in the wholesale and retail trades, including catering. Perhaps due to this high proportion of part-time workers in the workforce, the labour turnover in the food industry, particularly among production and non-regular workers, is one of the highest in all industries in Japan.(30) Having a flexible workforce is advantageous for firms in the confectionery branch, for example, which need to respond to quick changes in consumer taste and demand. A confectionery firm near Tokyo employs about 300 regular workers, in addition to between 400 and 500 non-regular workers as needed, the latter being part-time workers and contract-based temporary workers. At a dairy processing firm, the share of the part-time workers in the total workforce increased from 21.6 per cent in 1992 to 22.8 per cent in 1994.(31) Table 3.17 presents the number of employees and the proportion of part-time workers to total employees in the food, drink, animal feed and tobacco industries as well as in three food subsectors in Japan for the period 1992-96, by sex and size of establishment. Women accounted for the majority of the workforce in the sector as a whole, as well as in the seafood and bakery/confectionery branches. In fact, the seafood-processing workers were predominantly women. However, many women in the entire sector as well as in the three individual subsectors, were employed as part-time workers. Nearly half of the women workers in the bakery/confectionery subsector were in part-time employment, the proportion being the highest among the subsectors presented in the table. Moreover, the proportion of women part-time workers in this subsector continued to increase during the period presented, while it declined slightly from 1994 to 1996 for the entire sector as well as in seafood-processing. In the livestock subsector, however, the proportion declined from 1992 to 1994, but subsequently increased again.
The table shows that men are also being affected, though to a lesser extent than women, by the general trend towards increased flexibility. For example, the proportion of male part-time workers in the sector as a whole increased from 6.6 per cent in 1992 to 7 per cent in 1996 in smaller establishments and from 5.7 to 6.8 per cent in larger ones. For both men and women, the proportion of part-time workers was generally higher in smaller enterprises than larger ones, perhaps indicating that smaller firms need to be more flexible to be competitive. All in all, women workers are more vulnerable than men to the strategy of flexible labour input employed by enterprises, in terms of type of employment contract and employment security. Against the backdrop of the long practice of permanent employment security in Japan, particularly in large enterprises, today's trend of increased employment flexibility is also affecting more and more regular workers. One phenomenon is the declining number of production workers, who are increasingly being transferred to the sales divisions. At a large brewery, for example, the number of factory workers dropped from 2,346 in 1984 to 1,861 in 1993, while the number of administrative and sales workers climbed from 934 to 1,606 during the same period. With the sales divisions absorbing more workers, the linkage between production and retail is being strengthened.(32)
Table 3.17. Japan: Number
of employees and the proportion of part-time workers in food-processing industries,
by sex and size of establishment, 1992-96
Year |
Size |
Sex |
Food, drink, feed, tobacco |
Livestock products |
Seafood processing |
Bakery/confectionery |
||||
Employees1 |
Part-time |
Employees1 |
Part-time |
Employees1 |
Part-time |
Employees1 |
Part-time |
|||
1992 |
>5 |
Total |
1 252 |
23.9 |
150 |
22.9 |
222 |
23.4 |
289 |
30.0 |
>30 |
Total |
855 |
21.0 |
129 |
21.9 |
123 |
19.2 |
218 |
27.9 |
|
1994 |
>5 |
Total |
1 267 |
27.9 |
149 |
18.8 |
209 |
26.8 |
276 |
31.9 |
>30 |
Total |
890 |
26.7 |
127 |
15.8 |
125 |
28.0 |
213 |
29.6 |
|
1996 |
>5 |
Total |
1 312 |
26.9 |
151 |
21.9 |
215 |
24.2 |
286 |
33.9 |
>30 |
Total |
913 |
23.8 |
130 |
19.2 |
129 |
17.1 |
220 |
30.9 |
|
1 In thousands, annual average. 2
Proportion of part-time workers to total employees. |
||||||||||
Table 3.18 presents employment in the FDT industries in the United Kingdom by sex, category of worker and percentage change for the period 1993-96. Although men far outnumbered women among full-time workers, women accounted for a large proportion of part-time workers, as in Japan. While the number of full-time workers declined more or less continuously, the percentage decline among female full-time workers was greater than that of male full-time workers. On the other hand, the share of part-time workers, which had dropped in 1994 and 1995, recovered in 1996. While the number of male part-time workers increased steadily, that of female part-time workers declined until 1995, after which it increased again. The table shows that the labour market situation in the food, drink and tobacco industries has become increasingly flexible. Flexibility is also being encouraged by the Government of the United Kingdom as it is expected to create more employment opportunities, both temporary and permanent. Flexible employment includes part-time work, job-sharing, temporary work, telework, work from or at home and annualized work, all of which allow businesses to adapt their workforce to the fluctuating product demand, rather than having to pay idle workers during slack seasons. Many favour employment flexibility on the grounds that it enables workers to combine work with other activities, such as rearing and caring for family members. It is estimated that only 13 per cent of part-time workers are in their current form of employment because of their inability to find permanent jobs.(33)
Table 3.18. United Kingdom:
Employment in the food, drink and tobacco industries, by sex, category of worker
and percentage change, 1993-96 (thousands; 1993 = 100)
Year |
Full-time workers |
Part-time workers |
Grand total |
||||
Men |
Women |
Total |
Men |
Women |
Total |
||
1993 |
273.3 |
123.5 |
396.7 |
9.8 |
54.3 |
64.1 |
460.8 |
1994 |
265.7 (97.2) |
118.7 (96.1) |
384.4 (96.9) |
10.4 (106.1) |
51.2 (94.3) |
61.6 (94.1) |
446.0 (96.8) |
1995 |
269.3 (98.5) |
117.8 (95.4) |
387.1 (97.6) |
11.1 (113.3) |
48.9 (90.1) |
60.0 (93.6) |
447.1 (97.0) |
1996 |
266.1 (97.4) |
115.5 (93.5) |
381.6 (96.2) |
11.4 (116.3) |
52.8 (97.2) |
64.2 (100.2) |
445.8 (96.7) |
Source: Office for National Statistics, United Kingdom: Food, drink and tobacco sector review (Quarter 2, 1996); and J.A. Burns with Marian Garcia: The impact of technical change on employment in the UK food and drink industries, project for the ILO (University of Reading, July 1997), p. 28. |
|||||||
Table 3.19 gives a breakdown of employment in the FD industries in Belgium by sex and category of workers for the period 1991-95. The total number of both manual and non-manual workers declined in both the food and drink industries. The decline was greatest in the drink industry being -20.6 per cent for manual workers and -15 per cent for non-manual workers, with the corresponding figures in the food industry being -5.6 per cent for manual workers and -2.2 per cent for non-manual workers. Among these groups of workers, the female manual workers in the drink industry were the most negatively affected, their percentage decline being 27.3 per cent, followed by their male colleagues in the same industry (-20.3 per cent) and female manual workers in the food industry (-11 per cent). Non-manual workers in both industries and male manual workers in the food industry were less affected. In fact, the number of female non-manual workers in the food industry grew by 12 per cent during the period under consideration, leading to the impression that having more qualifications might mean greater employment security.
Table 3.20 presents a breakdown of FD employment in the United States. It shows, inter alia, that the absolute number and the proportion of women workers increased in the bakery and bread/cake branches, despite a decline in the total workforce in these branches; and that in the whole sector the proportion of production workers is increasing, as indicated in table 3.9 presented earlier. It is interesting to note, however, that the number of production workers has declined in most of the companies where workers are affiliated with the Bakery, Confectionery and Tobacco Workers' International Union (BCTWIU).
Table 3.19. Belgium: Employment
in the food and drink industries, by sex and category of worker, 1991-95
Industry |
Year |
Manual workers |
Non-manual workers |
Total |
||||
Men |
Women |
Subtotal |
Men |
Women |
Subtotal |
|||
Food |
1991 |
39 864 |
16 612 |
56 476 |
10 698 |
10 873 |
21 571 |
78 047 |
1992 |
39 656 |
16 239 |
55 895 |
10 505 |
10 814 |
21 319 |
77 214 |
|
1993 |
39 082 |
15 323 |
54 405 |
10 263 |
10 841 |
21 104 |
75 509 |
|
1994 |
38 972 |
14 904 |
53 876 |
10 156 |
11 244 |
21 400 |
75 276 |
|
1995 |
39 115 |
14 768 |
53 883 |
10 327 |
12 154 |
22 481 |
76 364 |
|
Drink |
1991 |
7 982 |
348 |
8 330 |
3 162 |
1 067 |
4 229 |
12 559 |
1992 |
7 693 |
301 |
7 994 |
3 193 |
1 081 |
4 274 |
12 268 |
|
1993 |
7 287 |
278 |
7 565 |
3 091 |
1 087 |
4 178 |
11 743 |
|
1994 |
6 715 |
272 |
6 987 |
3 071 |
1 049 |
4 120 |
11 107 |
|
1995 |
6 364 |
253 |
6 617 |
2 983 |
1 033 |
4 016 |
10 633 |
|
Source: Commission consultative de l'Alimentation (Conseil central de l'économie), on the basis of ONSS data (Brussels); Office national de sécurité sociale (ONSS): Effectifs des employeurs et des travailleurs assujettis à la sécurité sociale au 30 juin 1991, 1992, 1993 (Brussels). |
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Table 3.20. United States:
Employment trends in the food industry, 1990-96 (thousands)
Food |
Workforce |
Women |
% of women |
Production workers |
1990 |
1 660.5 |
539.8 |
32.5 |
1 193.8 (71.9) |
1991 |
1 669.9 |
540.3 |
32.4 |
1 205.2 (72.2) |
1992 |
1 662.5 |
540.1 |
32.5 |
1 211.9 (72.9) |
1993 |
1 675.6 |
541.2 |
32.3 |
1 225.1 (73.1) |
1994 |
1 678.0 |
547.0 |
32.5 |
1 230.9 (73.4) |
1995 |
1 680.4 |
553.0 |
32.9 |
1 238.0 (73.7) |
1996 |
1 692.6 |
556.0 |
32.8 |
1 254.1 (74.1) |
Bakery |
||||
1990 |
213.0 |
64.6 |
30.3 |
133.3 (62.6) |
1991 |
212.9 |
63.9 |
30.0 |
134.3 (63.1) |
1992 |
208.3 |
63.8 |
30.6 |
133.8 (64.2) |
1993 |
210.1 |
64.6 |
30.7 |
135.6 (64.5) |
1994 |
212.0 |
67.8 |
31.9 |
138.9 (65.5) |
1995 |
209.2 |
69.8 |
33.3 |
139.9 (66.9) |
1996 |
210.1 |
n.a. |
n.a. |
141.7 (67.4) |
Bread/cake |
||||
1990 |
155.6 |
37.5 |
24.1 |
89.1 (57.3) |
1991 |
155.0 |
36.8 |
23.7 |
89.8 (57.9) |
1992 |
149.2 |
36.0 |
24.1 |
88.4 (59.2) |
1993 |
150.3 |
36.5 |
24.2 |
89.6 (59.6) |
1994 |
151.3 |
38.4 |
25.3 |
91.3 (60.3) |
1995 |
147.2 |
38.9 |
26.4 |
90.4 (61.4) |
1996 |
148.7 |
n.a. |
n.a. |
91.2 (61.3) |
n.a. = Not available. |
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The utilization of non-regular workers is also quite common in many other countries. For example, Nestlé's plant in Punjab, India, had a workforce of 720 permanent workers in 1996 which was augmented by some 2,500 casual contract workers during the peak season. One of the Pakistani plants under the same management as the Punjab plant employed 25 per cent of its workforce on a casual basis, while one-third of the workforce at a further plant in Pakistan under the same management consisted of casual workers.(34)
In addition to having more recourse to part-time and casual work as forms of flexible employment, an increasing number of firms now outsource so-called peripheral activities, such as cleaning, transport, catering, maintenance, training and data processing. This permits firms to free up their resources as part of their drive for increased flexibility, while they concentrate on the activities where they have a competitive advantage. It is argued that peripheral activities can also be better performed by those who specialize in them. Another reason behind increased outsourcing may be that it allows those who would be employers in a traditional worker-employer relationship to shift industrial relations responsibility to a third party.(35)
The case-study(36) on outsourcing maintenance work undertaken on Australia-based enterprises included a dairy firm with 304 employees and a brewery with 417 workers, which had employed 32 and 73 maintenance workers respectively. These two companies cited "cost reduction" as one of the reasons for outsourcing as it enabled them to totally eliminate or significantly reduce the number of maintenance workers as well as overtime hours, while increasing flexibility in the allocation and type of work performed. The other reasons included the resolving of demarcation disputes and the improving of the industrial relations. Both firms pointed out that demarcation issues had been a major problem prior to outsourcing maintenance work. In the past, for example, production workers had not been permitted to do any maintenance work, even of a simple, routine nature, while skilled workers had performed only the work corresponding to their qualifications. This rigid demarcation in the workplace had limited the flexible deployment of the workforce in response to fluctuating demand and changing needs. With a significant or total reduction in maintenance staff, the two firms reported an increase in overall labour productivity. This was in spite of the fact that the retrenched employees had been awarded redundancy payments exceeding the minimum legal provisions and that it would take at least two years or more for the firms to recover the one-off costs associated with outsourcing. The study also noted a few points of concern. First, the level of service declined and machine down time increased as preventive maintenance was being neglected, second, the whole process of outsourcing, including redundancy payments, was costly; and third, while industrial relations might have been improved in general, absenteeism and labour turnover showed little change. The study thus questions whether outsourcing is always advisable.
Nevertheless, outsourcing has become more common as companies, particularly in industrialized countries, seek to become leaner. This trend is also gradually spreading to developing countries. A workers' organization in Ghana, for example, reported that security and general cleaning services were increasingly being outsourced in the plants whose workers it represented. An employers' organization in Nigeria, on the other hand, found its affiliated members taking a middle course between the two extremes of total outsourcing and internal sourcing as far as maintenance work was concerned. Their decisions were based on the consideration of the significance of the particular maintenance service and the quality and cost of external services available.(37)
Changing work
organization
and new skill requirements
Various degrees of demarcation, to separate different categories of workers, with those at the lower end of the hierarchy following the decisions made by managers and supervisors, has been the traditional method of work organization found in most factories. Today, there is a growing move away from this type of organization, as an increasing number of companies are adopting a new form of work organization in their continuous search for higher productivity.
This new form of work organization places more emphasis on workers with multiple and advanced skills who participate fully in flexible, innovative teamwork with an ownership-based motivational approach, where hierarchical layers are reduced to facilitate consultation, and decisions are increasingly taken at the team level. The new system, combined with annualized work hours and continuous rotating shifts, aims at improving quality and reducing wastage through teamwork such as quality control circles (QCCs) and total quality management (TQM) programmes. The new structure thus has the elements of job enlargement (e.g. introducing multiple skills and job rotation), technical job-enrichment (e.g. giving workers with appropriate training the responsibility of monitoring product quality through statistical feedback on monitoring panels and deciding on necessary adjustments or minor corrections) and social enrichment (e.g. reducing the hierarchical layers and increasing participation in decision-making at the team level to provide a greater sense of responsibility and motivation).(38)
According to the results of a case-study(39) undertaken on a Cadbury's chocolate factory where the new form of work organization had been introduced, many responsibilities previously held at managerial or supervisory level have been transferred to shop-floor workers. The tasks of quality monitoring and necessary adjustments and corrections based on statistical feedback have also been given to appropriately trained operators. A four-shift pattern has been established, using four teams of 30 operators per shift, one team covering chocolate processing, another covering wrapping and the two others working on packing lines. The personalities and skill levels of individual operators have been taken into consideration when forming each team, which functions without a leader or detailed supervision. Craft workers provide the teams with expertise as and when required. At this plant, all the maintenance work, minor and routine, used to be undertaken by dedicated maintenance workers. Now, routine work such as machine cleaning and minor fault corrections is increasingly performed by operators. Craft workers have also gained flexible and multiple skills across the old mechanical-electrical skill boundary, though major electrical work is still carried out by trained electricians with appropriate qualifications. The new form of work organization has also created quality action teams (QATs), consisting of technicians, craft workers and operators who meet regularly to discuss and resolve any pending issues, such as details of specifications and layout of new machinery that the company may be considering installing.
The case-study(40) on some Mexican FD manufacturers reports that a bean-canning firm introduced the "total quality and permanent improvement programme" in 1992 with the aim of improving both product and human resource management. The objectives of the programme were to raise worker awareness of the importance of improving quality to reduce al