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Technology and employment

Far more studies have been undertaken on the effects of alternative or appropriate technology on employment than on the effects of appropriate products. The notion of technological fixity and rigid production functions dates back to the classic article by Richard Eckaus [18], in which he showed how substitution possibilities between capital and labour were limited in the industrial sector. He argued that in general there was only one efficient technique for producing a well defined industrial product. This technique would be mostly capital-intensive and would be imported from industrialized countries. At the time when he wrote, little empirical evidence existed to challenge this assertion. However, during the 1970s and 1980s a substantial number of empirical micro-industrial case-studies dealing mainly with consumer goods, but also to a lesser extent with intermediate and capital goods sectors, clearly pointed towards wide technological choice [6, 65, 48, 71]. The range of choice is broader for crude products and for simple consumer goods industries than for those requiring high degrees of precision and quality product specifications. Nevertheless, in these latter cases, as noted above, there is evidence to suggest that the technological determinist view is exaggerated.

One attractive approach to technology and employment during the 1970s was offered by Sen [57]. Policy implications of technology choice are linked to the production and employment modes, viz. family employment, extended family, wage employment, and cooperatives. The technological sophistication increases with the mode of production/employment. For example, technologies that can be economical for wage-based firms are unlikely to be available to small household production units. With an increasing emphasis on private sector development and growth of small enterprises, a comparative analysis of technology choice by employment modes seems, on the surface, to represent a fruitful enquiry.

One has to be careful about making hasty generalizations on the basis of a very micro and heterogeneous sample of industrial and agricultural case-studies. There is clearly a dilemma here. As noticed earlier, aggregative studies tend to blur the issue of technology choice made essentially at the micro level of firms and farms; they also tend to underestimate the employment effects. But at the same time? small-scale micro studies do not lend themselves to easy generalizations.

Notwithstanding the above caveat, some general conclusions can be drawn from the wealth of empirical case-studies listed in table 1.

First, the studies show that factor price distortions (of only two factors, capital and labour), while relevant to technology decision-making, are not as important as many other factors. Furthermore, two-factor models that consider the role of factor pricing are somewhat oversimplified. In cases such as processing industries like sugar, the prices of raw material inputs may be more important in the choice of technology.

Second, even when factor pricing policies play a role as incentives or disincentives, they may not be sufficient for appropriate technology decisions. They would be more effective if combined with such measures as the establishment of appropriate institutions of technological information collection and dissemination, appropriate infrastructure and adequate planning, organization and implementation machinery, etc.

Third, the choice of technology is significantly influenced by the existing market structures and the associated issues of risk and uncertainty. The risk and uncertainty may arise due to imperfect knowledge about alternative technologies. The monopolistic advantages of a firm or industry are more likely to encourage the choice of capital-intensive technology than the more competitive structures.

Table 1 Coverage of empirical studies on technology choice in manufacturing

Product or industry Author Country or regiona Technology characteristics covered
Scale Product Skills Raw material Material handling, transport Factor efficiency Location Energy Employment Environment Used machinery
Consumer goods                          
Beer brewing ILO and Strathclyde -   x x x x x     x   x
Bread ILO and Strathclyde -           x     x    
Bread ILO Kenya x       x x         x
Can-making ILO Kenya,                      
    Thailand x x x x x x x       x
Cane sugar production ILO - x   x     x          
Clothing Michigan Sierra Leone x x   x   x          
Coconut oil production ILO - x   x x x x     x    
Cotton spinning Yale Brazil       x x x     x   x
Fish preservation ILO -   x x x   x          
Fruit, vegetable preservation ILO - x x x x   x   x x    
Gerri production from cassava ILO - x x x x x x   x x    
Jute processing ILO Kenya x x x x x x x        
Leather shoes ILO Malaysia           x          
Leather shoes Yale Brazil x x x x x x   x      
Maize milling ILO and Strathclyde - x x x x   x   x      
Milk processing ILO - x x x x   x   x      
Rice milling ILO and Strathclyde Tanzania x x x x   x   x x x  
Salt production Enos South-East Asia x x x x   x   x x    
Sugar processing ILO India x x x x   x   x x    
Sugar processing Strathclyde Ghana,                      
    Ethiopia x x x x   x   x x    
Textiles ILO United Kingdom x   x     x          
Textiles Strathclyde Africa x   x   x x          
Intermediate goods                          
Bricks ILO Malaysia x x     x x x x x    
Cement blocks ILO Kenya x x x x x x x x      
Copper and aluminium ILO -   x   x   x     x    
Fertilizers Strathclyde India         x   x x      
Iron foundries Strathclyde - x x x                
Nuts and bolts Strathclyde - x x x x   x     x    
Capital goods                          
Agric. Machineryc Mitra - x x x     x x x x    
Engineering ILO Colombia x x     x x         x
Metal working ILO Mexico x x   x       x      

Source: Ref. 6.

a. Dash indicates that the study is based on international cross-section data.
b. Ref. 20.
c. Ref. 44.

Fourth, substitution between skilled and unskilled labour, and supervisory and management costs hinder the use of labour-intensive technologies. Substitutions take place not only between capital and labour but also between semi-skilled labour and skilled supervisory plus unskilled labour. Our stock of empirical knowledge about the skill implications of alternative technologies remains quite limited.

Finally, sociocultural and political forces, vested interests of decision makers, and government intervention may facilitate or hinder the use of more appropriate technologies.

The issues of energy saving and environmental conservation have also come to the forefront in recent years. This has raised the number of criteria against which technology decisions need to be judged. As noted in table 1, few of the existing studies consider environmental effects and energy consumption as important variables in technology choice [6]. Far too much emphasis in early studies was placed on the issues of employment and income distribution, although these are a major concern of developing countries.

The analysis of a relationship between technology, environment, and employment is of recent origin [46, 8]. It is therefore not surprising that even in the industrialized countries, it is difficult to find many good studies that attempt to analyse quantitatively (or even qualitatively) possible trade-offs between energy intensity, labour intensity, and pollution intensity of alternative industrial technologies. One of the major difficulties in undertaking such analyses is not so much the vagueness of definitions of environmental considerations as the lack of adequate data about polluting and non-polluting technologies and industries.

The bulk of the literature on technology choice in the 1970s was of a static nature, examining issues of technology choice at a point in time rather than the dynamic effects - social as well as economic - of technical change over a period of time. While some studies have been done to examine how technology changes take place and what effect they have on the modification of known techniques [2, 59, 61], the stock of empirical knowledge on the subject still remains relatively limited. Yet historical studies of technical change are essential to guide the planners and policy makers in making intertemporal choices regarding growth of output and employment. When the short- and long-term effects of choices differ, the policy makers are better advised about politically and socially feasible lower cost solutions.

There is another context in which the dynamic issues of technology development are relevant. One of the major objectives of developing countries is to develop indigenous technological capacity, not only to select from existing alternatives but to widen the choice by developing new ones. A prerequisite for this is that at least some technological development activity be located in developing countries to ensure positive effects of domestic learning and to promote self-reliant attitudes. These issues came to the fore in the 1980s and are examined in the next section.

The 1980s: Macro issues, new technologies, and capabilities

Macroeconomic aspects of technology choice
New technologies and blending
Technological capabilities

In the 1980s, the evolution of development thinking shifted to more macroeconomic and sectoral aspects of technology policy and its implementation. These issues were somewhat complicated by the emergence during this period of new technological innovations like microelectronics, telecommunications, and biotechnologies, whose potential influences on production, income distribution, and employment are not easily foreseen. I first examine issues of macroeconomic effects of technology choice and their policy implications before examining the potential effects of new technologies and technology blending.

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