TMFDI/1998 - Part 3

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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

Part 3

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Over the past 200 years millions of jobs have been replaced by machines.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.

Employment trends

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.

Industrialized countries

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. Source: Institut für Arbeitsmarkt und Berufsforschung der Bundesanstalt für Arbeit: Berufe im Spiegel der Statistik, Beschäftigung und Arbeitslosigheit, Beschäftigung und Arbeitslosigheit, Nrnberg, Germany, 1996-97), p. 440.

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 ('000)	Production workers²	Employees ('000)	Production workers²	Employees ('000)	Production workers²

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. ² Proportion of production workers to all employees. Source: US Department of Labor, Bureau of Labor Statistics: Employment and earnings (Washington, DC, Jan. 1993, Jan. 1995 and Dec. 1996).

Developing countries

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. Source: Veena Nabar: Technology and employment in Indian food and drinks industry: Some case-studies (New Delhi, July 1997), unpublished paper, p. 42.

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
Food	Establishments	42	40	39	44	45

Drink	Workers	25 428	24 716	22 362	21 244	14 633
Drink	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 growth rate, 1986-92	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 workers²	Employees¹	Part-time workers²	Employees¹	Part-time workers²	Employees¹	Part-time workers²

1992	>5	Total Men Women	1 252 580 671	23.9 6.6 38.8	150 81 69	22.9 7.3 41.3	222 65 157	23.4 7.7 29.9	289 137 151	30.0 9.2 48.9
1992	>30	Total Men Women	855 436 419	21.0 5.7 37.0	129 72 57	21.9 6.3 41.5	123 38 84	19.2 7.6 24.5	218 112 106	27.9 9.2 47.8
1994	>5	Total Men Women	1 267 562 706	27.9 7.3 44.5	149 77 72	18.8 2.6 36.1	209 58 151	26.8 6.9 34.4	276 121 155	31.9 8.3 50.3
1994	>30	Total Men Women	890 419 471	26.7 6.4 44.8	127 69 58	15.8 2.9 32.8	125 36 89	28.0 2.8 38.2	213 99 114	29.6 8.1 48.2
1996	>5	Total Men Women	1 312 598 714	26.9 7.0 43.6	151 86 66	21.9 3.5 43.9	215 61 153	24.2 6.6 31.4	286 130 156	33.9 9.2 54.5
1996	>30	Total Men Women	913 442 471	23.8 6.8 39.9	130 75 55	19.2 4.0 40.0	129 37 92	17.1 2.7 22.8	220 106 114	30.9 9.4 50.9
¹ In thousands, annual average. ² Proportion of part-time workers to total employees. Source: Ministry of Labour, Japan: Monthly Labour Survey, National Survey, Dec. 1992, 1994 and 1996.

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).

Table 3.20. United States: Employment trends in the food industry, 1990-96 (thousands)


Food	Workforce	Women	% of women	Production workers (% of total)

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. Source: US Department of Labor, as cited in information provided by the Bakery, Confectionery and Tobacco Workers' International Union (AFL-CIO), Summer 1997.

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

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