- Email: [email protected]
Agricultural distortions and structural change
Journal of Asian Economics 24 (2013) 17–25
Contents lists available at SciVerse ScienceDirect
Journal of Asian Economics
Agricultural distortions and structural change Richard Grabowski * Department of Economics, Southern Illinois University, Carbondale, IL 62901, United States
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 January 2012 Received in revised form 7 October 2012 Accepted 14 October 2012 Available online 23 October 2012
Many developing countries have chosen to use a variety of policy instruments to transfer resources out of agriculture and to the manufacturing and, in some countries, the service sector. It will be argued in this paper that such policies slow structural change, create incentives for capital intensive production in non-agricultural sectors, and slow the process of technical innovation in agriculture. These arguments will be illustrated by examining the recent growth experience in India. ß 2012 Elsevier Inc. All rights reserved.
JEL classification: O10 O13 Keywords: Structural change Agriculture Policy distortions
Rapid economic development is now occurring in a number of regions in the world. Most strikingly, both China and India are experiencing sustained rapid growth and this is in turn having positive spillover effects on much of the rest of the world. Rapid growth in these regions has been accompanied by a change in the composition of production with agricultural production as a share of GDP shrinking while manufacturing and, in some cases, services as a share of GDP increasing. The structural change in the composition of GDP has also been accompanied by a shift in employment. That is, the growth process has usually been accompanied by an expansion of labor intensive non-agricultural activities (manufacturing) which draws labor out of the agricultural sector resulting in a decline in agricultural employment as a share of total employment. This structural change is seen by many scholars as being an important stage in the growth and development process. Productivity (labor productivity) in the non-agricultural sectors is generally higher than in agriculture. Thus structural change involves shifting labor out of low productivity occupations and into high productivity occupations resulting in an increase in overall growth. In addition, this shift in employment is generally thought to be the key to rapid poverty reduction in developing countries (Mcmillan & Rodrik, 2011). It is the process of structural change, outlined above, which will be the main focus of this paper. More specifically, it will be the structural shift in employment from agriculture to non-agriculture that will play a pivotal role in the analysis which will follow. It is hypothesized that productivity growth in the agricultural sector is the key to structural change in the development process. In other words, the more rapid productivity growth in agriculture the more rapid structural change in employment will be and vice versa. Most developing nations (including much of South America, Africa, and Asia) have in the past engaged in import substitution policies which ostensibly were aimed at promoting rapid development. However, it will be argued here that
* Tel.: +1 618 453 5067. E-mail address: [email protected]. 1049-0078/$ – see front matter ß 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.asieco.2012.10.002
18
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
such policies were actually driven by the states need for tax revenue. Import substitution policies transferred resources from hard to tax sectors (agriculture and other informal sector operations) to easier to tax sectors (formal sector manufacturing and services). Thus these policies acted as a heavy, implicit tax on agricultural production. A number of implications for development can be drawn from the analysis in this paper. Those countries which continue to engage in the implicit taxation of the agricultural sector are likely to find structural change retarded and overall growth slowed. However, even countries which engage in reform which eliminates or reduces the implicit taxation of agriculture are also likely to face problems. This is due to the fact that past policies will have disrupted the agricultural research process and structure. Thus technological change (productivity growth) is likely to continue to be dramatically slowed, even after reform. The implication is that structural change will be slowed, even though growth may be enhanced by the reform. The reforms are likely to promote more rapid growth in the non-agricultural sectors, but the transfer of labor will be slowed. Thus overall poverty reduction is also likely to be reduced. The analysis will be illustrated with a discussion of the experience of India. After World War II, India followed an import substitution strategy, which implicitly taxed the agricultural sector. The result was sluggish growth and structural change. The economic reforms of the 1980s and 1990s slowly reduced the implicit tax on the agricultural sector. This stimulated rapid growth in non-agricultural sectors, but agricultural productivity stagnated. As a result, structural change in employment has still been slow. The experiences of India will also be briefly compared with those of several other Asian countries. 1. Import substitution and agricultural distortions After World War II many newly independent nations in Asia and Africa sought to carry out programs which would dramatically increase their rates of economic growth. Most of these countries chose to embark upon import substitution strategies of growth. Import substitution policies often combined tariff protection with a number of other policies. Exchange rates were often overvalued. This would make the importation of capital cheaper and thus allow for additional investments. However, in order to manage the foreign exchange imbalances that resulted required complex systems of foreign exchange controls to be imposed. These types of policies were followed in Brazil from 1945 to 1964 and also in much of the rest of Latin America (Lyne, 2006). In some countries, such as India (Kochhar et al., 2006), licensing rules were used to try to guide investment into those areas which the state deemed important for the long-run development of the country. Also state controlled institutions were sometimes utilized to keep the prices of food staples cheap so as to keep wages from rising and thus reducing the profit of industry (thought to be the main sources of savings). No matter the economic impact of these policies, economic theorists (such as Baier, 1972) believed that a state acting as a social planner could act in the best interests of society at large so as to promote rapid economic growth for the country (Shapiro & Taylor, 1990). However, as evidence mounted that there were significant problems with this strategy of development some scholars (Grossman & Helpman, 1994) began to argue that the view that the state could act as a social planner, whose goal was to maximize growth, was seriously flawed. Instead, it was argued, for example by Grossman and Helpman (1994), that groups within society put pressure on the state to provide policies favorable to their own parochial interests even if it comes at the expense of the interests of society in general. Thus tariffs are imposed or licensing laws created by the state so as to provide benefits to powerful interests. These approaches one can label as political economy explanations. Gordon and Li (2009) have questioned the political economy explanations of the policy combinations discussed above. Instead they suggest that taking a perspective focusing on taxation in developing countries can go a long way toward understanding policy making. They focus on the fact that most developing countries have large informal sectors and firms in these sectors avoid government regulation and taxation and carry out a large proportion of transactions on a cash basis. Thus the sector is invisible and unrecognized by the formal institutional structure of the nation. There are many informal sector firms in urban areas, but large parts of agricultural production fall within the informal sector. The model that Gordon and Li (2009) develop is based on the assumption that when firms utilize the formal sector and other formal sector institutions, they create records and that the state can utilize these records to determine tax liability and enforce tax laws. Firms can choose to operate in the formal sector, using modern institutions, financial services, and infrastructure or the informal sector where services and infrastructure are not available. Of course, in the informal sector the advantage is that they do not have to pay taxes or abide by regulations. If the returns from utilizing formal sector institutions and financial services are relatively low compared to the cost of taxes that have to be paid and regulations that must be followed, then many firms will choose to operate in the informal sector. Certain types of firms are less likely to leave the formal sector. In particular, capital intensive firms and firms heavily dependent on modern services are less likely to shift to the informal sector. They are more willing to pay taxes and submit to regulation. As a result tax authorities come to be dependent for tax revenue on these types of firms. Thus the state in many developing countries becomes dependent on a small, capital intensive sub-sector of its economy for tax revenue. How is the state to raise the increased revenue that it is likely to need? The argument is that the state will likely utilize policies which reallocate resources away from the informal and toward the formal sector where they can be taxed. Gordon and Li (2009) show that there are a number of policies which can be utilized to achieve this goal. Tariffs and quotas can be utilized to protect capital intensive, formal sector firms. These policies enhance their profitability and thus their taxability. Exchange rate controls allow the state to allocate valuable foreign exchange to formal sector firms,
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
19
enhancing their profitability and taxability. Internal controls over the banking system can allow the state to direct credit to the formal sector with the same impact on profitability and taxability. Public ownership of large, capital intensive, formal sector firms is the most direct mechanism for raising revenue since the state has direct information on profits which allows for taxation with little resistance. All of these policies allow resources to be transferred from hard to tax sectors to easy to tax sectors. Agriculture makes up a large part of the hard to tax, less formal sector. According to Rajaraman (2005) agriculture is rated as the hardest to tax (of all hard to tax sectors) due to the small scale and spatial spread of the activity and the need for state contingent levies, given the intrinsic vulnerability of agriculture to exogenous shocks. Historically some nations, such as Japan during the Meiji period, relied heavily on a land tax. This was an institution inherited from the feudal past. For today’s developing countries taxing this sector is very difficult. Thus most of these policies extract resources from agriculture and transfer them to the non-agricultural sector. As a result, agriculture is discriminated against via policy so as to promote the expansion of easier to tax economic activity. On top of these sorts of indirect forms of resource extraction from agriculture, many states have also sought to use more direct methods as well. This usually involves the state behaving as a monopsonist with respect to the purchasing of agricultural commodities from the agricultural sector. The monopsony power is then used to force down the price of these agricultural commodities so as to provide cheap food and raw materials to the formal sector. The policy induced distortions aimed at agriculture have a broader effect on the economy and on the rate at which structural change can occur in the economy. Intuition would indicate that such policies would lead to an increase in the production of non-agricultural goods relative to agricultural goods. This would occur naturally as economic growth occurred and Engel’s law comes into effect. However, these policies would tend to cause a more rapid rate of structural change in terms of production. However, there is a second dimension to structural change having to do with employment. One might be tempted to conclude that the policies discussed above would also lead to a faster transfer of labor out of the agricultural and into non-agricultural sectors. But this is not necessarily the case. The impact of such policies on structural change in terms employment is analyzed in the work of Dennis and I˙s¸can (2011). They construct a model composed of two sectors, agriculture and non-agriculture. The nominal rate of protection (NRP) is used as a measure of the distortions in policy directed at agriculture. This measures the percentage by which the local producer price is above or below the border or international price. If it is positive, this implies that agriculture is being subsidized via policy and if it is negative then agriculture is being discriminated against in terms of policy. The model utilized by Dennis and I˙s¸can (2011) implies that agricultural policies go a long way in terms of explaining the differences in the rate at which labor is reallocated from agriculture to non-agriculture. They argue that policies which discriminate against agriculture slow this reallocation of labor process via three paths. First, many farmers in developing countries operate at close to subsistence. Thus policies which in effect tax the agricultural sector (discriminate against agriculture) damage the ability of these farmers to survive in the long-run. They will have to devote more labor to agricultural production. In addition, these farmers are going to be less willing to utilize new technology. While new technology might raise the average level of productivity, it also exposes farmers to greater risk. As a result, farmers will seek to devote more time to production. Second, the bias against agriculture will reduce the ability of farmers to purchase nonagricultural goods for consumption again slowing the reallocation of labor out of agriculture. Finally, discrimination against the agricultural sector reduces disposable income and thus the savings and investment that farmers can undertake. This will reduce the demand for non-agricultural inputs (machinery) and thus reduce the demand for labor required by the producers of these non-agricultural inputs. Policies which discriminate against agriculture have several additional impacts not discussed by Dennis and I˙s¸can (2011). If the reader will remember, the main reason for engaging in policies which discriminate against the agricultural sector is to transfer resources from a hard tax sector to an easy tax sector of the economy. The ease of taxing the latter stems from the capital intensive nature of the production process. Capital intensity implies that firms in this sector are dependent upon the services of the financial sector and thus information is readily available on revenues, etc. This makes taxation much easier. The implication then is that policies biased against agriculture are used to subsidize the expansion of the capital intensive sector of the economy. As a result, growth in this sector will likely be more rapid and structural change in terms of the composition of production is likely to occur. However, the capital intensity of production will likely slow structural change in terms of employment. In addition to the above, discrimination against agriculture also disrupts the development of new technology for the agricultural sector. The development of agricultural technology through research and development is thought to be subject to significant market failure. Often those who invest in the development of new agricultural technology cannot capture all of the benefits generated by that research and thus there is significant free riding. The private benefits of such research are significantly below the social benefits. Of course, this is the result of the lack of institutions that allow for the internalization of all the benefits generated by research. However, for biochemical innovations it is very difficult to create property rights to protect new ideas in this area. In addition, in poor countries such institutions rarely exist and if they exist they often do not function well (Alstron, Pardey, & Roseboom, 1998). Second, the nature of this research activity is long term, large scale, and subject to significant risk. This implies that typical firms (farms) are not capable of undertaking such research. Third, the benefits of such research often occur to future generations which have little influence on the allocation of resources. Given the above, the public sector has often played a significant role in agricultural investments. Ruttan and Hayami (1998) developed the theory of induced innovation in order to analyze how this research process occurs. They argued that changes in relative factor prices (as well as output prices) influence the path of technical innovation. That is, in those
20
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
countries where labor (and fertilizer) is relatively abundant relative to capital, then research resources will be devoted to the development of technologies that are more labor intensive. Thus comparing Japan and the U.S., the former’s agricultural development was characterized by the development of labor intensive, biochemical technologies while the latter followed a more mechanical technology path. Hayami and Ruttan argue that the induced innovation process will still operate if there exists effective interaction among farmers, public research institutions, and private agricultural supply firms. More specifically, as particular constraints become binding in farmers they will press the public research institutions to develop new technologies and push agricultural supply firms to provide the critical inputs that substitute for these factors that are becoming increasingly scarce. ‘‘Perceptive scientists and science administrators respond by making available new technical possibilities and new inputs that enable farmers profitably to substitute the increasingly abundant factors for increasingly scarce factors, thereby guiding the demand of farmers for unit cost reductions in a socially optimum direction’’ (p. 169). The dialectical interaction between farmers and the research institution is likely to be most effective when farmers are organized into politically effective association and the research institutions are highly decentralized. One can see that policies biased against the agricultural sector will likely have very long term implications. The construction of a research bureaucracy is difficult to do, especially for poor countries, and often farmers have little influence on political decisions concerning the allocation of resources. However, these difficulties are magnified dramatically when government policies discriminate against the agricultural sector. Such policies are likely to result in less public investment in the development of an institutional structure devoted to agricultural research. Because agriculture is viewed as a low priority scientists and researchers within the existing research institution have few incentives to respond to the needs and problems faced by farmers. Finally, policies biased against agriculture push farmers away from commercialization thus reducing the likelihood that common economic problems will create common political interests, thus reducing collective action possibilities. Thus discrimination against the agricultural sector is likely to have several impacts all of which are likely to slow structural change in terms of employment shares. The next section will illustrate the above ideas through a discussion of the Indian experience. 2. Indian experience After World War II, newly independent India followed an import substitution strategy of economic development very similar to that followed by many other developing countries. Tariffs and quotas were used to protect particular industries from foreign competition. The Indian currency was often overvalued and exchange rate controls were used to allocate scarce foreign exchange. A number of industries were actually owned by the state since they were deemed to be very important for the growth of India to be left in private hands. Also licensing regulations were utilized in order to try to guide investment into particular areas of the economy. More specifically, after independence almost all manufactured goods ‘‘were subject to discretionary import licensing or were canalized through government monopoly trading organizations’’ (Pursell, Gulati, & Gupta, 2009, p. 352). After 1956 import licensing was tightened whenever the foreign exchange situation worsened. By 1966 tariffs on imported manufactured goods reached very high levels. Although both tariffs and licensing were relaxed after the devaluation of 1966, by 1968 licensing was once again strengthened and imports of nearly all manufactured goods were barred. Empirical evidence ‘‘suggests that trade policies during this period led to terms of trade that were highly unfavorable for agriculture relative to manufacturing (Pursell et al., 2009, p. 352). In 1985 a new policy was promoted which led to a steady devaluation of the Indian currency. However, domestic agricultural prices continued to move independent of changes in border prices. ‘‘In manufacturing, during the 1980s, domestic prices were similarly delinked from international prices by the import licensing system and high tariffs that averaged over 100%’’ (Pursell et al., 2009, p. 354). In addition to the typical policy combination, India developed some additional policies which were peculiar to India. The political leaders sought to avoid undue concentration of economic power. As a result, several restrictions were placed on the expansion of large firms. In addition, significant benefits were provided to small scale firms and some products were exclusively reserved for production by the small scale sector. Significant protections were provided to workers in larger firms which included restrictions on the ability of these firms to fire workers. Finally, ‘‘for a poor country India spent and still spends, relatively far more resources on higher education than on primary education’’ (Kochhar et al., 2006, p. 984). The analysis in the previous section argued that these types of policies would result in significant discrimination against agriculture and that this discrimination effectively transfers resources out of the agricultural sector and toward nonagriculture. The empirical work of Gulati and Pursell (2008) is very useful in analyzing this issue. They calculate nominal rates of assistance to agriculture as well as relative rates of assistance for agriculture (RRA). The former measures the extent to which government policies have raised or lowered the returns to agricultural producers above or below what they would have received without government intervention. The latter measures the extent to which the tradable parts of agricultural production are subsidized or taxed relative to the producers of non-agricultural goods. Thus NRA includes the effects of policies directly aimed at agriculture. This measure includes the effects of input subsidies (to such inputs as fertilizer and electricity), however it does not incorporate the effects of preferential interest rates. The RRA adds the effects of import substitution policies which protect the non-agricultural sector via tariffs, etc. If the estimates for NRA or RRA are negative this implies that agriculture is being taxed and thus resources are being transferred out.
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
21
Table 1 Agricultural distortions. Year
NRA
RRA
1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
20 2 5 13 0 8 17 19 6 36 28 1 5 6 3 9 15 6 13 15 29 32 43 14 8 16 0 12 1 4 7 7 2 11 8 9 17 26 16 11
56 55 56 61 53 37 13 16 52 73 64 38 35 43 39 53 50 29 22 13 25 32 40 19 20 11 12 16 9 13 24 22 16 1 2 3 28 19 1 na
Adapted from Gulati and Pursell (2008).
The results of the calculations by Gulati and Pursell (2008) are presented in Table 1. Examining the results for NRA one can see that there is no clear cut pattern. In the early 1970s, discriminatory policies were clearly transferring resources from agriculture. This occurs sporadically throughout the period 1965–2004. Remember, this incorporates policies which tend to directly raise or lower the returns to production in agriculture, such as policies aimed at influencing product or input prices. However, examining the results for RRA reveals a consistent pattern. From 1965 to 1999 (except 1985–1987) the numbers are persistently negative. Government policies have consistently extracted resources from the agricultural sector and transferred them to the non-agricultural sector. This has generally been the result of government policies aimed at protecting the non-agricultural sector relative to the agricultural sector. There are several implications which follow from the above. One would expect that such policies biased against agriculture would slow the process of structural change, as measured by proportion of the population employed in agriculture, in India. Examining Table 2 one can see that from 1951 to the 1980s there was only a very small fall in the share of agriculture in total employment. This corresponds to the years of heavy taxation of agriculture illustrated in Table 1. From the early 1980s to 2010 the drop is much more rapid and this corresponds to the period of time in Table 1 during which the extent of agricultural taxation significantly declined. One can compare India’s experience with that of other Asian countries. In China approximately the same percentage (68%) was employed in agriculture in the 1980s, but by 2000 this had fallen to 47%. At the same time the RRA in China fell from 60.5 to 0.9. In Thailand the proportion of employment in agriculture fell from 70% to 48% while its RRA fell from 27.5 to 7.4. By 2000 the proportion of employment in agriculture in Indonesia had fallen to 45% while Indonesia’s RRA for agriculture rose to 5.4. In other words, agriculture was subsidized (Anderson & Martin, 2007; Kochhar, Kumar, Rajan, Subramanian, & Tokatlidis, 2006).
22
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
Table 2 Proportion of population employed in agriculture. Year
Employment share of agriculture (%)
1951 1961 1972–1973 1977–1978 1983 1987–1988 1993–1994 1999–2000 2009–2010
74.6 76.2 73.9 71 68.6 65 64.7 59.9 51.3
Adapted from Barga (2005) and Papola and Sahu (2012).
Thus India’s performance is similar to a number of other countries, but the reduction in agricultural employment has been slower relative to these other nations. This could be due to the fact that investment in agricultural technology has slowed, thus slowing agricultural growth. In addition, the institutions governing employment in India generally increase the cost of labor thus causing production in manufacturing and services to be more capital intensive. This would certainly slow the rate of structural change (Kochhar et al., 2006). This conclusion is further supported by the work of Headey, Bezemer, and Hazell (2008). They empirically examined the correlations between two measures of structural change (percent of population urbanized and non-agricultural employment share) and GDP per capita for a large group of developing countries. They found that the relationship was nonlinear in character. This suggests that initially as per capita income rises urbanization and non-agricultural employment shares rise rapidly, but this slows dramatically at higher per capita GDP levels. Most importantly, the results indicate that the two structural change variables for India are substantially below what, an average, other countries at similar levels of income have generated. This is true for a number of Asian countries. The above results are further supported by the work of Kochhar et al. (2006). They analyzed the characteristics of the Indian economy in the 1980s and in the 2000s. The initial years would reflect the impacts of the import substitution strategy initially followed by India while the latter years would reflect the impacts of the policy liberalization period. The employment shares for industry and services in India are compared to that for a sample of developed and developing countries utilizing regression analysis, while taking into account GDP per capita (and correcting for country size). The findings indicate that in the 1980s the employment share of services in India was substantially below that of other developing (once corrections are made for country size, land area, and income), while the employment share in manufacturing was not an outlier. The implication then is that the employment share of agriculture was substantially larger in India than for countries of similar size and GDP per capita. This continued to hold in the year 2000. That is, India’s share of employment in manufacturing is not statistically significantly different from that of countries of similar size and GDP per capita, while the share of employment in services is statistically significantly less than countries of similar size, and GDP per capita. This in turn implies that the share of employment in agriculture is higher than in countries of similar size and GDP per capita. In addition to the above, Kochhar et al. (2006) find that India’s manufacturing sector was concentrated in skill and capital intensive rather than labor intensive production. ‘‘India had a greater presence in industries that required scale (and capital) than other developing countries . . .’’ (p. 982). Finally, while the growth in services from 1980 to 2000 had been rapid, the rate of growth in employment in this sector was very low. Additional evidence concerning the employment share of agriculture in India is provided by the work of Foster and Rosenzeig (2010). They collected a panel data set at the plot and at the farm level, from 1999 to 2008, on inputs, outputs, and investments. The data were taken from surveys administered in 17 of the major states of India. The main implication of their work is that they find that Indian agriculture is characterized by surplus of labor and they further estimate that 22% of the agricultural labor is surplus in nature. However, their notion of surplus labor is very different from that concept as it has traditionally been used in development economics. In their analysis the estimate is based upon how much labor would be needed if the current size distribution of landholdings could be altered via land consolidation. This is important because economies of scale exist in Indian agriculture. Specifically, they find that larger, more mechanized firms are more efficient than smaller more labor intensive farms. The point here is not that land consolidation should be pushed as a means of eliminating surplus labor. If a country in which neither growth in manufacturing or services generates rapid enough employment growth to absorb this surplus labor, this is not a viable policy. Instead, the idea here is that the analysis presented in the previous section of this paper implied that significant implicit and explicit taxation of agriculture slowed the structural transformation (in terms of employment) and there is certainly evidence in support of the notion that such transformation has been very slow in India. Much labor remains stranded in agriculture. 3. The impact on agricultural technology Not only was structural change in terms of employment directly slowed as the result of significant taxation of the agricultural sector, but the system of public research in agriculture was also constrained. If the reader will remember,
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
23
Table 3 Growth in real public expenditure. Period
Agricultural research and education
Extension and training
1960s 1970s 1980s 1990–2005
6.5 9.5 6.3 4.8
10.7 0.1 7.0 2.0
Adapted from Ramakumar (2010).
according to the induced innovation theory of Ruttan and Hayami (1998) the public sector plays a significant role in agricultural research and extension and policies aimed at taxing agriculture are likely to limit investment in technological change. Thus even when reforms occur that reduce or eliminate agricultural taxation (as has occurred to some extent in India), the effects of long previous periods of heavy taxation are likely to persist through a reduced rate of technical change in agriculture. Thus structural change in terms of employment is likely to be slow even after periods of reform. In terms public spending aimed at technical innovation, it is probably expenditures on agricultural research and development that are most important to consider. Public expenditures on agricultural research were 1.6 billion rupees in 1965 (measured in 1995 prices) and increased to 7.1 billion in 1990. This amounted to an annual growth rate of 5.8%. This resulted in the release of a number of new seed varieties and the adoption of these high yielding varieties reached close to 50% by 1990. However, by 1995 government spending on agricultural research and development increased very little relative to 1990. As a percentage of agricultural GDP, research spending increased from 0.l2% in 1964 to 0.50% in 1987. After 1987 stagnation set in and this percentage dropped to 0.43 in 1995. This is low in comparison with other developing countries which average 0.75% (Fan, Gulati, & Thorat, 2007). More recent data concerning these issues is provided in the work of Ramakumar (2010). Looking at Table 3, one can see the growth rates for agricultural research and education and for rural extension and training. In terms of research and development, the growth rate rises to 9.5% in the 1970s and then declines dramatically to 4.8% from 1990 to 2005. The growth in rural extension and training declines to 2% in the period 1990–2005. The implication of the above is that public support for the innovation process in agriculture has declined over the last several decades. If the reader will remember, it was argued in the previous section that this was what one would expect to occur as policies biased against agriculture reduce the resources available to the agricultural sector. The impact on agricultural growth and technical innovation is apparent by examining Table 4. As can be seen, growth rates of production and yields have tumbled in the last several decades reflecting the slowing of agricultural research in India. Recent work by Nin-Pratt, Yu, and Fan (2010) adds additional insight. They compare productivity growth in Indian agriculture to that of China for the period 1961–2004. They use a frontier approach to construct a Malmquist measure of productivity growth. This allows them to measure total factor productivity improvements over time, but also allows them to disaggregate such improvements into that due to efficiency improvement and that due to technological change. The results are summarized in Table 5. For China the pre-reform period was prior to 1978 while for India it was prior to 1990. During the pre-reform period China (under Mao) invested significantly in agricultural technology development, however the effects of this investment were offset by the highly discriminatory distortionary policies levied on the agricultural sector (Bramall, 2000). This investment continued throughout the post-reform period as well. However, in India public investment in new agricultural technology slowed Table 4 Growth rates of production and yield. Production 1949/1950 to 1964/1965
Yield 1967/1968 to 1980/1981
1981/1982 to 1991/1992
1992/1993 to 2005/2006
1949/1950 to 1964/1965
1967/1968 to 1980/1981
1981/1982 to 1991/1992
1992/1993 to 2005/2006
Food grains Cereals Rice Wheat Jowar Bigra Maize Pulses Oilseeds Fruit and vegetables Non-food grains
2.90 3.40 3.50 4.00 2.50 2.30 3.90 1.40 3.40 1.90
2.20 2.60 2.20 5.20 2.60 0.80 0.60 0.20 1.00 4.20
2.90 3.20 3.90 3.30 0.10 1.50 2.60 1.30 5.80 4.00
0.64 1.13 0.80 1.33 3.71 1.42 3.60 0.24 0.66 2.90
1.40 1.90 2.10 1.30 1.50 1.20 1.20 0.20 0.60 1.80
1.90 1.70 1.50 2.60 3.50 0.30 0.50 0.70 0.70 2.00
3.21 3.10 3.30 3.10 1.80 2.30 2.50 1.10 2.20 2.20
0.84 0.79 0.99 0.64 1.18 2.04 1.93 0.04 0.91 1.24
3.50
2.40
4.30
1.26
0.90
1.30
2.60
0.73
All crops
3.10
2.30
3.40
1.15
1.30
1.70
2.90
1.02
Adapted from Ramakumar (2010).
24
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
Table 5 Agricultural indicators (% growth rates). India
China Pre-reform
Reform
Pre-reform
Reform
Total factor productivity Technical change Efficiency
2.70 1.10 3.80
3.40 0.90 2.50
0.42 0.17 0.59
0.54 0.32 0.22
Yield crops Output/land Output/worker Total Ag output
3.70 2.70 2.10 3.80
2.00 3.60 3.70 4.70
2.10 2.40 1.0 2.30
2.10 2.50 1.3 2.50
Total inputs Labor Workers/1000 ha
7.10 1.70 0.60
1.20 0.90 0.10
3.10 1.40 1.30
2.0 1.20 1.20
Nin-Pratt et al. (2010).
considerably (as discussed above). Looking at the pre-reform periods in both China and India one can see that total factor productivity growth was negative in both countries prior to reform. This was mainly due to the growth of inefficiency in both. Part of this negative impact was offset by technical change for both, but in China the rate of technical change is much higher. Reform in China and India took different forms. In China the reforms were initially focused on rural areas and involved institutional reforms which dramatically increased incentives for farm families. In India, the reforms were focused on eliminating protectionist policies aimed at the non-agricultural sector. Both sets of reforms had positive effects in each country. The efficiency of production in China improved dramatically while technical innovation remained high. Output per worker rose dramatically and workers per 1000 ha of land declined. For India the results were much more modest. Technical change rose a bit, technical efficiency improved a bit, and thus total factor productivity rose modestly. Although output grew at 2.50%, this was mainly due to increased input usage. Workers per 1000 ha continued to grow. 4. Summary and conclusions Agriculture in India has proven very difficult to tax. Much of this sector can be seen as being informal in nature, meaning that although many farmers lack access to services such as credit and marketing, they are able to avoid explicit taxation. This has meant that the Indian state has been dependent on raising tax revenue from formal sector firms. These are capital intensive firms that rely heavily on services provided by the formal sector (banking, finance, etc.). This leaves a trail of records which makes them easier to tax. In order to enhance tax revenue, the Indian state engaged in import substitution strategies which would transfer resources from hard to tax sectors (agriculture) to easy to tax sectors (non-agriculture). The impact on the agricultural sector has been negative. It was argued in this paper the policies biased against agriculture would slow structural change in terms of employment. This occurs because discriminatory policies threaten the standard of living of farmers. The poorest must therefore devote more labor to agricultural production. In addition, they will be reluctant to utilize new technology slowing productivity growth requiring that additional labor be kept in agriculture. Finally, discrimination also reduces the saving and investment that can occur in agriculture, reducing the demand for non-agricultural production. All this slows the transfer of workers from agriculture to non-agriculture. These effects are enhanced by two others. First, discrimination against agriculture represents the subsidizing of capital intensive, non-agricultural production which will in turn slow the creation of jobs there and slow structural transformation in terms of employment. Second, discrimination against the agricultural sector tends to cause the public research institutions devoted to agriculture to deteriorate over time. This further slows the growth of agricultural productivity which in turn keeps labor in the countryside. These ideas were illustrated by reviewing the experience of India. Indeed import substitution policies caused significant transfers of resources out of agriculture. Although the intensity of this effect declined with the reforms of the 1990s, this discrimination continued until 2000. From several perspectives, it is also apparent that the shift in employment from agriculture to non-agriculture has been slowed as a result. The non-agricultural sector in India seems inordinately capital and skill intensive for a country abundant in unskilled labor. In addition, investments in the agricultural research institutions have declined over the last several decades. As a result, technical innovation has been slowed. References Alstron, J. M., Pardey, P. G., & Roseboom, J. (1998). Financing agricultural research: International investment patterns and policy perspectives. World Development, 26, 1057–1071. Anderson, K., & Martin, W. (2007). Distortions to agricultural incentives in Asia. Washington, DC: World Bank. (Agricultural distortions working paper 59). Baier, W. (1972). Import substitution and industrialization in Latin America: Experiences and expectations. Latin America Research Review, 7, 95–122.
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
25
Barga, R. (2005). Critical issues in India’s service led growth. New Delhi: Indian Council for Research on International Economic Relations. Bramall, C. (2000). Sources of Chinese economic growth, 1978–1996. Oxford: Oxford University Press. Dennis, B. N., & I˙s¸can, T. B. (2011). Agricultural distortions, structural change, and economic growth: A cross-country analysis. American Journal of Agricultural Economics, 93, 885–905. Fan, S., Gulati, A., & Thorat, S. (2007). Investment, subsidies, and pro-poor growth in rural India. IFPRI discussion paper 00716. Foster, A., & Rosenzeig, M.R. (2010). Is there surplus labor in rural India. Yale Economic Department working paper no. 85. Gordon, R., & Li, W. (2009). Tax structures in developing countries: Many puzzles and a possible explanation. Journal of Public Economics, 93, 855–866. Grossman, G., & Helpman, E. (1994). Protection for sale. American Economic Review, 84, 855–866. Gulati, A., & Pursell, G. (2008, September). Distortions to agricultural incentives in India and other south Asia. Washington, DC: World Bank Development Research Group. (Agricultural distortions working paper 63). Headey, D., Bezemer, D., & Hazell, P. (2008). Agricultural exit problems: Causes and consequences. IFPRI discussion paper 00802, International Food Policy Research Institute, Washington, DC. Kochhar, K., Kumar, U., Rajan, R., Subramanian, A., & Tokatlidis, I. (2006). India’s pattern of development: What happened, what follows. Journal of Monetary Economics, 53, 981–1019. Lyne, M. W. (2006). Rethinking the political economy of import substitution industrialization: Not rent seeking but clientelism. Columbia, South Carolina: Department of Political Science, University of South Carolina. Mcmillan, M., & Rodrik, D. (2011). Globalization, structural change, and productivity growth. NBER working paper no. 17143. Nin-Pratt, A., Yu, B., & Fan, S. (2010). Comparisons of agricultural productivity growth in China and India. Journal of Productivity Analysis, 33, 209–223. Papola, T. S., & Sahu, P. P. (2012). Growth and structure of employment in India. New Delhi: Institute for Studies in Industrial Development. Pursell, G., Gulati, A., & Gupta, K. (2009). India in distortions to agricultural incentives in Asia. pp. (339–378) Washington, DC: The World Bank. Rajaraman, I. (2005). Taxing agriculture in a developing country: A possible approach. In B. H. Baltagi & E. Saddka (Eds.), Taxing the hard to tax: A possible approach (pp. 245–268). Emerald Group Publishing Unlimited. Ramakumar, R. (2010). Continuity and change: Notes on agriculture in ‘New India’. In A. D’Costa (Ed.), A New India? Reflections in the long twentieth century (pp. 43– 70). London and New York: Anthem Press. Ruttan, V. W., & Hayami, Y. (1998). Induced innovation model of agricultural development. In C. K. Eicher & J. M. Staatz (Eds.), International Agricultural Development (pp. 163–180). Baltimore: Johns Hopkins University Press. Shapiro, H., & Taylor, L. (1990). The state and industrial strategy. World Development, 18, 861–878.
Contents lists available at SciVerse ScienceDirect
Journal of Asian Economics
Agricultural distortions and structural change Richard Grabowski * Department of Economics, Southern Illinois University, Carbondale, IL 62901, United States
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 January 2012 Received in revised form 7 October 2012 Accepted 14 October 2012 Available online 23 October 2012
Many developing countries have chosen to use a variety of policy instruments to transfer resources out of agriculture and to the manufacturing and, in some countries, the service sector. It will be argued in this paper that such policies slow structural change, create incentives for capital intensive production in non-agricultural sectors, and slow the process of technical innovation in agriculture. These arguments will be illustrated by examining the recent growth experience in India. ß 2012 Elsevier Inc. All rights reserved.
JEL classification: O10 O13 Keywords: Structural change Agriculture Policy distortions
Rapid economic development is now occurring in a number of regions in the world. Most strikingly, both China and India are experiencing sustained rapid growth and this is in turn having positive spillover effects on much of the rest of the world. Rapid growth in these regions has been accompanied by a change in the composition of production with agricultural production as a share of GDP shrinking while manufacturing and, in some cases, services as a share of GDP increasing. The structural change in the composition of GDP has also been accompanied by a shift in employment. That is, the growth process has usually been accompanied by an expansion of labor intensive non-agricultural activities (manufacturing) which draws labor out of the agricultural sector resulting in a decline in agricultural employment as a share of total employment. This structural change is seen by many scholars as being an important stage in the growth and development process. Productivity (labor productivity) in the non-agricultural sectors is generally higher than in agriculture. Thus structural change involves shifting labor out of low productivity occupations and into high productivity occupations resulting in an increase in overall growth. In addition, this shift in employment is generally thought to be the key to rapid poverty reduction in developing countries (Mcmillan & Rodrik, 2011). It is the process of structural change, outlined above, which will be the main focus of this paper. More specifically, it will be the structural shift in employment from agriculture to non-agriculture that will play a pivotal role in the analysis which will follow. It is hypothesized that productivity growth in the agricultural sector is the key to structural change in the development process. In other words, the more rapid productivity growth in agriculture the more rapid structural change in employment will be and vice versa. Most developing nations (including much of South America, Africa, and Asia) have in the past engaged in import substitution policies which ostensibly were aimed at promoting rapid development. However, it will be argued here that
* Tel.: +1 618 453 5067. E-mail address: [email protected]. 1049-0078/$ – see front matter ß 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.asieco.2012.10.002
18
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
such policies were actually driven by the states need for tax revenue. Import substitution policies transferred resources from hard to tax sectors (agriculture and other informal sector operations) to easier to tax sectors (formal sector manufacturing and services). Thus these policies acted as a heavy, implicit tax on agricultural production. A number of implications for development can be drawn from the analysis in this paper. Those countries which continue to engage in the implicit taxation of the agricultural sector are likely to find structural change retarded and overall growth slowed. However, even countries which engage in reform which eliminates or reduces the implicit taxation of agriculture are also likely to face problems. This is due to the fact that past policies will have disrupted the agricultural research process and structure. Thus technological change (productivity growth) is likely to continue to be dramatically slowed, even after reform. The implication is that structural change will be slowed, even though growth may be enhanced by the reform. The reforms are likely to promote more rapid growth in the non-agricultural sectors, but the transfer of labor will be slowed. Thus overall poverty reduction is also likely to be reduced. The analysis will be illustrated with a discussion of the experience of India. After World War II, India followed an import substitution strategy, which implicitly taxed the agricultural sector. The result was sluggish growth and structural change. The economic reforms of the 1980s and 1990s slowly reduced the implicit tax on the agricultural sector. This stimulated rapid growth in non-agricultural sectors, but agricultural productivity stagnated. As a result, structural change in employment has still been slow. The experiences of India will also be briefly compared with those of several other Asian countries. 1. Import substitution and agricultural distortions After World War II many newly independent nations in Asia and Africa sought to carry out programs which would dramatically increase their rates of economic growth. Most of these countries chose to embark upon import substitution strategies of growth. Import substitution policies often combined tariff protection with a number of other policies. Exchange rates were often overvalued. This would make the importation of capital cheaper and thus allow for additional investments. However, in order to manage the foreign exchange imbalances that resulted required complex systems of foreign exchange controls to be imposed. These types of policies were followed in Brazil from 1945 to 1964 and also in much of the rest of Latin America (Lyne, 2006). In some countries, such as India (Kochhar et al., 2006), licensing rules were used to try to guide investment into those areas which the state deemed important for the long-run development of the country. Also state controlled institutions were sometimes utilized to keep the prices of food staples cheap so as to keep wages from rising and thus reducing the profit of industry (thought to be the main sources of savings). No matter the economic impact of these policies, economic theorists (such as Baier, 1972) believed that a state acting as a social planner could act in the best interests of society at large so as to promote rapid economic growth for the country (Shapiro & Taylor, 1990). However, as evidence mounted that there were significant problems with this strategy of development some scholars (Grossman & Helpman, 1994) began to argue that the view that the state could act as a social planner, whose goal was to maximize growth, was seriously flawed. Instead, it was argued, for example by Grossman and Helpman (1994), that groups within society put pressure on the state to provide policies favorable to their own parochial interests even if it comes at the expense of the interests of society in general. Thus tariffs are imposed or licensing laws created by the state so as to provide benefits to powerful interests. These approaches one can label as political economy explanations. Gordon and Li (2009) have questioned the political economy explanations of the policy combinations discussed above. Instead they suggest that taking a perspective focusing on taxation in developing countries can go a long way toward understanding policy making. They focus on the fact that most developing countries have large informal sectors and firms in these sectors avoid government regulation and taxation and carry out a large proportion of transactions on a cash basis. Thus the sector is invisible and unrecognized by the formal institutional structure of the nation. There are many informal sector firms in urban areas, but large parts of agricultural production fall within the informal sector. The model that Gordon and Li (2009) develop is based on the assumption that when firms utilize the formal sector and other formal sector institutions, they create records and that the state can utilize these records to determine tax liability and enforce tax laws. Firms can choose to operate in the formal sector, using modern institutions, financial services, and infrastructure or the informal sector where services and infrastructure are not available. Of course, in the informal sector the advantage is that they do not have to pay taxes or abide by regulations. If the returns from utilizing formal sector institutions and financial services are relatively low compared to the cost of taxes that have to be paid and regulations that must be followed, then many firms will choose to operate in the informal sector. Certain types of firms are less likely to leave the formal sector. In particular, capital intensive firms and firms heavily dependent on modern services are less likely to shift to the informal sector. They are more willing to pay taxes and submit to regulation. As a result tax authorities come to be dependent for tax revenue on these types of firms. Thus the state in many developing countries becomes dependent on a small, capital intensive sub-sector of its economy for tax revenue. How is the state to raise the increased revenue that it is likely to need? The argument is that the state will likely utilize policies which reallocate resources away from the informal and toward the formal sector where they can be taxed. Gordon and Li (2009) show that there are a number of policies which can be utilized to achieve this goal. Tariffs and quotas can be utilized to protect capital intensive, formal sector firms. These policies enhance their profitability and thus their taxability. Exchange rate controls allow the state to allocate valuable foreign exchange to formal sector firms,
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
19
enhancing their profitability and taxability. Internal controls over the banking system can allow the state to direct credit to the formal sector with the same impact on profitability and taxability. Public ownership of large, capital intensive, formal sector firms is the most direct mechanism for raising revenue since the state has direct information on profits which allows for taxation with little resistance. All of these policies allow resources to be transferred from hard to tax sectors to easy to tax sectors. Agriculture makes up a large part of the hard to tax, less formal sector. According to Rajaraman (2005) agriculture is rated as the hardest to tax (of all hard to tax sectors) due to the small scale and spatial spread of the activity and the need for state contingent levies, given the intrinsic vulnerability of agriculture to exogenous shocks. Historically some nations, such as Japan during the Meiji period, relied heavily on a land tax. This was an institution inherited from the feudal past. For today’s developing countries taxing this sector is very difficult. Thus most of these policies extract resources from agriculture and transfer them to the non-agricultural sector. As a result, agriculture is discriminated against via policy so as to promote the expansion of easier to tax economic activity. On top of these sorts of indirect forms of resource extraction from agriculture, many states have also sought to use more direct methods as well. This usually involves the state behaving as a monopsonist with respect to the purchasing of agricultural commodities from the agricultural sector. The monopsony power is then used to force down the price of these agricultural commodities so as to provide cheap food and raw materials to the formal sector. The policy induced distortions aimed at agriculture have a broader effect on the economy and on the rate at which structural change can occur in the economy. Intuition would indicate that such policies would lead to an increase in the production of non-agricultural goods relative to agricultural goods. This would occur naturally as economic growth occurred and Engel’s law comes into effect. However, these policies would tend to cause a more rapid rate of structural change in terms of production. However, there is a second dimension to structural change having to do with employment. One might be tempted to conclude that the policies discussed above would also lead to a faster transfer of labor out of the agricultural and into non-agricultural sectors. But this is not necessarily the case. The impact of such policies on structural change in terms employment is analyzed in the work of Dennis and I˙s¸can (2011). They construct a model composed of two sectors, agriculture and non-agriculture. The nominal rate of protection (NRP) is used as a measure of the distortions in policy directed at agriculture. This measures the percentage by which the local producer price is above or below the border or international price. If it is positive, this implies that agriculture is being subsidized via policy and if it is negative then agriculture is being discriminated against in terms of policy. The model utilized by Dennis and I˙s¸can (2011) implies that agricultural policies go a long way in terms of explaining the differences in the rate at which labor is reallocated from agriculture to non-agriculture. They argue that policies which discriminate against agriculture slow this reallocation of labor process via three paths. First, many farmers in developing countries operate at close to subsistence. Thus policies which in effect tax the agricultural sector (discriminate against agriculture) damage the ability of these farmers to survive in the long-run. They will have to devote more labor to agricultural production. In addition, these farmers are going to be less willing to utilize new technology. While new technology might raise the average level of productivity, it also exposes farmers to greater risk. As a result, farmers will seek to devote more time to production. Second, the bias against agriculture will reduce the ability of farmers to purchase nonagricultural goods for consumption again slowing the reallocation of labor out of agriculture. Finally, discrimination against the agricultural sector reduces disposable income and thus the savings and investment that farmers can undertake. This will reduce the demand for non-agricultural inputs (machinery) and thus reduce the demand for labor required by the producers of these non-agricultural inputs. Policies which discriminate against agriculture have several additional impacts not discussed by Dennis and I˙s¸can (2011). If the reader will remember, the main reason for engaging in policies which discriminate against the agricultural sector is to transfer resources from a hard tax sector to an easy tax sector of the economy. The ease of taxing the latter stems from the capital intensive nature of the production process. Capital intensity implies that firms in this sector are dependent upon the services of the financial sector and thus information is readily available on revenues, etc. This makes taxation much easier. The implication then is that policies biased against agriculture are used to subsidize the expansion of the capital intensive sector of the economy. As a result, growth in this sector will likely be more rapid and structural change in terms of the composition of production is likely to occur. However, the capital intensity of production will likely slow structural change in terms of employment. In addition to the above, discrimination against agriculture also disrupts the development of new technology for the agricultural sector. The development of agricultural technology through research and development is thought to be subject to significant market failure. Often those who invest in the development of new agricultural technology cannot capture all of the benefits generated by that research and thus there is significant free riding. The private benefits of such research are significantly below the social benefits. Of course, this is the result of the lack of institutions that allow for the internalization of all the benefits generated by research. However, for biochemical innovations it is very difficult to create property rights to protect new ideas in this area. In addition, in poor countries such institutions rarely exist and if they exist they often do not function well (Alstron, Pardey, & Roseboom, 1998). Second, the nature of this research activity is long term, large scale, and subject to significant risk. This implies that typical firms (farms) are not capable of undertaking such research. Third, the benefits of such research often occur to future generations which have little influence on the allocation of resources. Given the above, the public sector has often played a significant role in agricultural investments. Ruttan and Hayami (1998) developed the theory of induced innovation in order to analyze how this research process occurs. They argued that changes in relative factor prices (as well as output prices) influence the path of technical innovation. That is, in those
20
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
countries where labor (and fertilizer) is relatively abundant relative to capital, then research resources will be devoted to the development of technologies that are more labor intensive. Thus comparing Japan and the U.S., the former’s agricultural development was characterized by the development of labor intensive, biochemical technologies while the latter followed a more mechanical technology path. Hayami and Ruttan argue that the induced innovation process will still operate if there exists effective interaction among farmers, public research institutions, and private agricultural supply firms. More specifically, as particular constraints become binding in farmers they will press the public research institutions to develop new technologies and push agricultural supply firms to provide the critical inputs that substitute for these factors that are becoming increasingly scarce. ‘‘Perceptive scientists and science administrators respond by making available new technical possibilities and new inputs that enable farmers profitably to substitute the increasingly abundant factors for increasingly scarce factors, thereby guiding the demand of farmers for unit cost reductions in a socially optimum direction’’ (p. 169). The dialectical interaction between farmers and the research institution is likely to be most effective when farmers are organized into politically effective association and the research institutions are highly decentralized. One can see that policies biased against the agricultural sector will likely have very long term implications. The construction of a research bureaucracy is difficult to do, especially for poor countries, and often farmers have little influence on political decisions concerning the allocation of resources. However, these difficulties are magnified dramatically when government policies discriminate against the agricultural sector. Such policies are likely to result in less public investment in the development of an institutional structure devoted to agricultural research. Because agriculture is viewed as a low priority scientists and researchers within the existing research institution have few incentives to respond to the needs and problems faced by farmers. Finally, policies biased against agriculture push farmers away from commercialization thus reducing the likelihood that common economic problems will create common political interests, thus reducing collective action possibilities. Thus discrimination against the agricultural sector is likely to have several impacts all of which are likely to slow structural change in terms of employment shares. The next section will illustrate the above ideas through a discussion of the Indian experience. 2. Indian experience After World War II, newly independent India followed an import substitution strategy of economic development very similar to that followed by many other developing countries. Tariffs and quotas were used to protect particular industries from foreign competition. The Indian currency was often overvalued and exchange rate controls were used to allocate scarce foreign exchange. A number of industries were actually owned by the state since they were deemed to be very important for the growth of India to be left in private hands. Also licensing regulations were utilized in order to try to guide investment into particular areas of the economy. More specifically, after independence almost all manufactured goods ‘‘were subject to discretionary import licensing or were canalized through government monopoly trading organizations’’ (Pursell, Gulati, & Gupta, 2009, p. 352). After 1956 import licensing was tightened whenever the foreign exchange situation worsened. By 1966 tariffs on imported manufactured goods reached very high levels. Although both tariffs and licensing were relaxed after the devaluation of 1966, by 1968 licensing was once again strengthened and imports of nearly all manufactured goods were barred. Empirical evidence ‘‘suggests that trade policies during this period led to terms of trade that were highly unfavorable for agriculture relative to manufacturing (Pursell et al., 2009, p. 352). In 1985 a new policy was promoted which led to a steady devaluation of the Indian currency. However, domestic agricultural prices continued to move independent of changes in border prices. ‘‘In manufacturing, during the 1980s, domestic prices were similarly delinked from international prices by the import licensing system and high tariffs that averaged over 100%’’ (Pursell et al., 2009, p. 354). In addition to the typical policy combination, India developed some additional policies which were peculiar to India. The political leaders sought to avoid undue concentration of economic power. As a result, several restrictions were placed on the expansion of large firms. In addition, significant benefits were provided to small scale firms and some products were exclusively reserved for production by the small scale sector. Significant protections were provided to workers in larger firms which included restrictions on the ability of these firms to fire workers. Finally, ‘‘for a poor country India spent and still spends, relatively far more resources on higher education than on primary education’’ (Kochhar et al., 2006, p. 984). The analysis in the previous section argued that these types of policies would result in significant discrimination against agriculture and that this discrimination effectively transfers resources out of the agricultural sector and toward nonagriculture. The empirical work of Gulati and Pursell (2008) is very useful in analyzing this issue. They calculate nominal rates of assistance to agriculture as well as relative rates of assistance for agriculture (RRA). The former measures the extent to which government policies have raised or lowered the returns to agricultural producers above or below what they would have received without government intervention. The latter measures the extent to which the tradable parts of agricultural production are subsidized or taxed relative to the producers of non-agricultural goods. Thus NRA includes the effects of policies directly aimed at agriculture. This measure includes the effects of input subsidies (to such inputs as fertilizer and electricity), however it does not incorporate the effects of preferential interest rates. The RRA adds the effects of import substitution policies which protect the non-agricultural sector via tariffs, etc. If the estimates for NRA or RRA are negative this implies that agriculture is being taxed and thus resources are being transferred out.
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
21
Table 1 Agricultural distortions. Year
NRA
RRA
1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
20 2 5 13 0 8 17 19 6 36 28 1 5 6 3 9 15 6 13 15 29 32 43 14 8 16 0 12 1 4 7 7 2 11 8 9 17 26 16 11
56 55 56 61 53 37 13 16 52 73 64 38 35 43 39 53 50 29 22 13 25 32 40 19 20 11 12 16 9 13 24 22 16 1 2 3 28 19 1 na
Adapted from Gulati and Pursell (2008).
The results of the calculations by Gulati and Pursell (2008) are presented in Table 1. Examining the results for NRA one can see that there is no clear cut pattern. In the early 1970s, discriminatory policies were clearly transferring resources from agriculture. This occurs sporadically throughout the period 1965–2004. Remember, this incorporates policies which tend to directly raise or lower the returns to production in agriculture, such as policies aimed at influencing product or input prices. However, examining the results for RRA reveals a consistent pattern. From 1965 to 1999 (except 1985–1987) the numbers are persistently negative. Government policies have consistently extracted resources from the agricultural sector and transferred them to the non-agricultural sector. This has generally been the result of government policies aimed at protecting the non-agricultural sector relative to the agricultural sector. There are several implications which follow from the above. One would expect that such policies biased against agriculture would slow the process of structural change, as measured by proportion of the population employed in agriculture, in India. Examining Table 2 one can see that from 1951 to the 1980s there was only a very small fall in the share of agriculture in total employment. This corresponds to the years of heavy taxation of agriculture illustrated in Table 1. From the early 1980s to 2010 the drop is much more rapid and this corresponds to the period of time in Table 1 during which the extent of agricultural taxation significantly declined. One can compare India’s experience with that of other Asian countries. In China approximately the same percentage (68%) was employed in agriculture in the 1980s, but by 2000 this had fallen to 47%. At the same time the RRA in China fell from 60.5 to 0.9. In Thailand the proportion of employment in agriculture fell from 70% to 48% while its RRA fell from 27.5 to 7.4. By 2000 the proportion of employment in agriculture in Indonesia had fallen to 45% while Indonesia’s RRA for agriculture rose to 5.4. In other words, agriculture was subsidized (Anderson & Martin, 2007; Kochhar, Kumar, Rajan, Subramanian, & Tokatlidis, 2006).
22
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
Table 2 Proportion of population employed in agriculture. Year
Employment share of agriculture (%)
1951 1961 1972–1973 1977–1978 1983 1987–1988 1993–1994 1999–2000 2009–2010
74.6 76.2 73.9 71 68.6 65 64.7 59.9 51.3
Adapted from Barga (2005) and Papola and Sahu (2012).
Thus India’s performance is similar to a number of other countries, but the reduction in agricultural employment has been slower relative to these other nations. This could be due to the fact that investment in agricultural technology has slowed, thus slowing agricultural growth. In addition, the institutions governing employment in India generally increase the cost of labor thus causing production in manufacturing and services to be more capital intensive. This would certainly slow the rate of structural change (Kochhar et al., 2006). This conclusion is further supported by the work of Headey, Bezemer, and Hazell (2008). They empirically examined the correlations between two measures of structural change (percent of population urbanized and non-agricultural employment share) and GDP per capita for a large group of developing countries. They found that the relationship was nonlinear in character. This suggests that initially as per capita income rises urbanization and non-agricultural employment shares rise rapidly, but this slows dramatically at higher per capita GDP levels. Most importantly, the results indicate that the two structural change variables for India are substantially below what, an average, other countries at similar levels of income have generated. This is true for a number of Asian countries. The above results are further supported by the work of Kochhar et al. (2006). They analyzed the characteristics of the Indian economy in the 1980s and in the 2000s. The initial years would reflect the impacts of the import substitution strategy initially followed by India while the latter years would reflect the impacts of the policy liberalization period. The employment shares for industry and services in India are compared to that for a sample of developed and developing countries utilizing regression analysis, while taking into account GDP per capita (and correcting for country size). The findings indicate that in the 1980s the employment share of services in India was substantially below that of other developing (once corrections are made for country size, land area, and income), while the employment share in manufacturing was not an outlier. The implication then is that the employment share of agriculture was substantially larger in India than for countries of similar size and GDP per capita. This continued to hold in the year 2000. That is, India’s share of employment in manufacturing is not statistically significantly different from that of countries of similar size and GDP per capita, while the share of employment in services is statistically significantly less than countries of similar size, and GDP per capita. This in turn implies that the share of employment in agriculture is higher than in countries of similar size and GDP per capita. In addition to the above, Kochhar et al. (2006) find that India’s manufacturing sector was concentrated in skill and capital intensive rather than labor intensive production. ‘‘India had a greater presence in industries that required scale (and capital) than other developing countries . . .’’ (p. 982). Finally, while the growth in services from 1980 to 2000 had been rapid, the rate of growth in employment in this sector was very low. Additional evidence concerning the employment share of agriculture in India is provided by the work of Foster and Rosenzeig (2010). They collected a panel data set at the plot and at the farm level, from 1999 to 2008, on inputs, outputs, and investments. The data were taken from surveys administered in 17 of the major states of India. The main implication of their work is that they find that Indian agriculture is characterized by surplus of labor and they further estimate that 22% of the agricultural labor is surplus in nature. However, their notion of surplus labor is very different from that concept as it has traditionally been used in development economics. In their analysis the estimate is based upon how much labor would be needed if the current size distribution of landholdings could be altered via land consolidation. This is important because economies of scale exist in Indian agriculture. Specifically, they find that larger, more mechanized firms are more efficient than smaller more labor intensive farms. The point here is not that land consolidation should be pushed as a means of eliminating surplus labor. If a country in which neither growth in manufacturing or services generates rapid enough employment growth to absorb this surplus labor, this is not a viable policy. Instead, the idea here is that the analysis presented in the previous section of this paper implied that significant implicit and explicit taxation of agriculture slowed the structural transformation (in terms of employment) and there is certainly evidence in support of the notion that such transformation has been very slow in India. Much labor remains stranded in agriculture. 3. The impact on agricultural technology Not only was structural change in terms of employment directly slowed as the result of significant taxation of the agricultural sector, but the system of public research in agriculture was also constrained. If the reader will remember,
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
23
Table 3 Growth in real public expenditure. Period
Agricultural research and education
Extension and training
1960s 1970s 1980s 1990–2005
6.5 9.5 6.3 4.8
10.7 0.1 7.0 2.0
Adapted from Ramakumar (2010).
according to the induced innovation theory of Ruttan and Hayami (1998) the public sector plays a significant role in agricultural research and extension and policies aimed at taxing agriculture are likely to limit investment in technological change. Thus even when reforms occur that reduce or eliminate agricultural taxation (as has occurred to some extent in India), the effects of long previous periods of heavy taxation are likely to persist through a reduced rate of technical change in agriculture. Thus structural change in terms of employment is likely to be slow even after periods of reform. In terms public spending aimed at technical innovation, it is probably expenditures on agricultural research and development that are most important to consider. Public expenditures on agricultural research were 1.6 billion rupees in 1965 (measured in 1995 prices) and increased to 7.1 billion in 1990. This amounted to an annual growth rate of 5.8%. This resulted in the release of a number of new seed varieties and the adoption of these high yielding varieties reached close to 50% by 1990. However, by 1995 government spending on agricultural research and development increased very little relative to 1990. As a percentage of agricultural GDP, research spending increased from 0.l2% in 1964 to 0.50% in 1987. After 1987 stagnation set in and this percentage dropped to 0.43 in 1995. This is low in comparison with other developing countries which average 0.75% (Fan, Gulati, & Thorat, 2007). More recent data concerning these issues is provided in the work of Ramakumar (2010). Looking at Table 3, one can see the growth rates for agricultural research and education and for rural extension and training. In terms of research and development, the growth rate rises to 9.5% in the 1970s and then declines dramatically to 4.8% from 1990 to 2005. The growth in rural extension and training declines to 2% in the period 1990–2005. The implication of the above is that public support for the innovation process in agriculture has declined over the last several decades. If the reader will remember, it was argued in the previous section that this was what one would expect to occur as policies biased against agriculture reduce the resources available to the agricultural sector. The impact on agricultural growth and technical innovation is apparent by examining Table 4. As can be seen, growth rates of production and yields have tumbled in the last several decades reflecting the slowing of agricultural research in India. Recent work by Nin-Pratt, Yu, and Fan (2010) adds additional insight. They compare productivity growth in Indian agriculture to that of China for the period 1961–2004. They use a frontier approach to construct a Malmquist measure of productivity growth. This allows them to measure total factor productivity improvements over time, but also allows them to disaggregate such improvements into that due to efficiency improvement and that due to technological change. The results are summarized in Table 5. For China the pre-reform period was prior to 1978 while for India it was prior to 1990. During the pre-reform period China (under Mao) invested significantly in agricultural technology development, however the effects of this investment were offset by the highly discriminatory distortionary policies levied on the agricultural sector (Bramall, 2000). This investment continued throughout the post-reform period as well. However, in India public investment in new agricultural technology slowed Table 4 Growth rates of production and yield. Production 1949/1950 to 1964/1965
Yield 1967/1968 to 1980/1981
1981/1982 to 1991/1992
1992/1993 to 2005/2006
1949/1950 to 1964/1965
1967/1968 to 1980/1981
1981/1982 to 1991/1992
1992/1993 to 2005/2006
Food grains Cereals Rice Wheat Jowar Bigra Maize Pulses Oilseeds Fruit and vegetables Non-food grains
2.90 3.40 3.50 4.00 2.50 2.30 3.90 1.40 3.40 1.90
2.20 2.60 2.20 5.20 2.60 0.80 0.60 0.20 1.00 4.20
2.90 3.20 3.90 3.30 0.10 1.50 2.60 1.30 5.80 4.00
0.64 1.13 0.80 1.33 3.71 1.42 3.60 0.24 0.66 2.90
1.40 1.90 2.10 1.30 1.50 1.20 1.20 0.20 0.60 1.80
1.90 1.70 1.50 2.60 3.50 0.30 0.50 0.70 0.70 2.00
3.21 3.10 3.30 3.10 1.80 2.30 2.50 1.10 2.20 2.20
0.84 0.79 0.99 0.64 1.18 2.04 1.93 0.04 0.91 1.24
3.50
2.40
4.30
1.26
0.90
1.30
2.60
0.73
All crops
3.10
2.30
3.40
1.15
1.30
1.70
2.90
1.02
Adapted from Ramakumar (2010).
24
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
Table 5 Agricultural indicators (% growth rates). India
China Pre-reform
Reform
Pre-reform
Reform
Total factor productivity Technical change Efficiency
2.70 1.10 3.80
3.40 0.90 2.50
0.42 0.17 0.59
0.54 0.32 0.22
Yield crops Output/land Output/worker Total Ag output
3.70 2.70 2.10 3.80
2.00 3.60 3.70 4.70
2.10 2.40 1.0 2.30
2.10 2.50 1.3 2.50
Total inputs Labor Workers/1000 ha
7.10 1.70 0.60
1.20 0.90 0.10
3.10 1.40 1.30
2.0 1.20 1.20
Nin-Pratt et al. (2010).
considerably (as discussed above). Looking at the pre-reform periods in both China and India one can see that total factor productivity growth was negative in both countries prior to reform. This was mainly due to the growth of inefficiency in both. Part of this negative impact was offset by technical change for both, but in China the rate of technical change is much higher. Reform in China and India took different forms. In China the reforms were initially focused on rural areas and involved institutional reforms which dramatically increased incentives for farm families. In India, the reforms were focused on eliminating protectionist policies aimed at the non-agricultural sector. Both sets of reforms had positive effects in each country. The efficiency of production in China improved dramatically while technical innovation remained high. Output per worker rose dramatically and workers per 1000 ha of land declined. For India the results were much more modest. Technical change rose a bit, technical efficiency improved a bit, and thus total factor productivity rose modestly. Although output grew at 2.50%, this was mainly due to increased input usage. Workers per 1000 ha continued to grow. 4. Summary and conclusions Agriculture in India has proven very difficult to tax. Much of this sector can be seen as being informal in nature, meaning that although many farmers lack access to services such as credit and marketing, they are able to avoid explicit taxation. This has meant that the Indian state has been dependent on raising tax revenue from formal sector firms. These are capital intensive firms that rely heavily on services provided by the formal sector (banking, finance, etc.). This leaves a trail of records which makes them easier to tax. In order to enhance tax revenue, the Indian state engaged in import substitution strategies which would transfer resources from hard to tax sectors (agriculture) to easy to tax sectors (non-agriculture). The impact on the agricultural sector has been negative. It was argued in this paper the policies biased against agriculture would slow structural change in terms of employment. This occurs because discriminatory policies threaten the standard of living of farmers. The poorest must therefore devote more labor to agricultural production. In addition, they will be reluctant to utilize new technology slowing productivity growth requiring that additional labor be kept in agriculture. Finally, discrimination also reduces the saving and investment that can occur in agriculture, reducing the demand for non-agricultural production. All this slows the transfer of workers from agriculture to non-agriculture. These effects are enhanced by two others. First, discrimination against agriculture represents the subsidizing of capital intensive, non-agricultural production which will in turn slow the creation of jobs there and slow structural transformation in terms of employment. Second, discrimination against the agricultural sector tends to cause the public research institutions devoted to agriculture to deteriorate over time. This further slows the growth of agricultural productivity which in turn keeps labor in the countryside. These ideas were illustrated by reviewing the experience of India. Indeed import substitution policies caused significant transfers of resources out of agriculture. Although the intensity of this effect declined with the reforms of the 1990s, this discrimination continued until 2000. From several perspectives, it is also apparent that the shift in employment from agriculture to non-agriculture has been slowed as a result. The non-agricultural sector in India seems inordinately capital and skill intensive for a country abundant in unskilled labor. In addition, investments in the agricultural research institutions have declined over the last several decades. As a result, technical innovation has been slowed. References Alstron, J. M., Pardey, P. G., & Roseboom, J. (1998). Financing agricultural research: International investment patterns and policy perspectives. World Development, 26, 1057–1071. Anderson, K., & Martin, W. (2007). Distortions to agricultural incentives in Asia. Washington, DC: World Bank. (Agricultural distortions working paper 59). Baier, W. (1972). Import substitution and industrialization in Latin America: Experiences and expectations. Latin America Research Review, 7, 95–122.
R. Grabowski / Journal of Asian Economics 24 (2013) 17–25
25
Barga, R. (2005). Critical issues in India’s service led growth. New Delhi: Indian Council for Research on International Economic Relations. Bramall, C. (2000). Sources of Chinese economic growth, 1978–1996. Oxford: Oxford University Press. Dennis, B. N., & I˙s¸can, T. B. (2011). Agricultural distortions, structural change, and economic growth: A cross-country analysis. American Journal of Agricultural Economics, 93, 885–905. Fan, S., Gulati, A., & Thorat, S. (2007). Investment, subsidies, and pro-poor growth in rural India. IFPRI discussion paper 00716. Foster, A., & Rosenzeig, M.R. (2010). Is there surplus labor in rural India. Yale Economic Department working paper no. 85. Gordon, R., & Li, W. (2009). Tax structures in developing countries: Many puzzles and a possible explanation. Journal of Public Economics, 93, 855–866. Grossman, G., & Helpman, E. (1994). Protection for sale. American Economic Review, 84, 855–866. Gulati, A., & Pursell, G. (2008, September). Distortions to agricultural incentives in India and other south Asia. Washington, DC: World Bank Development Research Group. (Agricultural distortions working paper 63). Headey, D., Bezemer, D., & Hazell, P. (2008). Agricultural exit problems: Causes and consequences. IFPRI discussion paper 00802, International Food Policy Research Institute, Washington, DC. Kochhar, K., Kumar, U., Rajan, R., Subramanian, A., & Tokatlidis, I. (2006). India’s pattern of development: What happened, what follows. Journal of Monetary Economics, 53, 981–1019. Lyne, M. W. (2006). Rethinking the political economy of import substitution industrialization: Not rent seeking but clientelism. Columbia, South Carolina: Department of Political Science, University of South Carolina. Mcmillan, M., & Rodrik, D. (2011). Globalization, structural change, and productivity growth. NBER working paper no. 17143. Nin-Pratt, A., Yu, B., & Fan, S. (2010). Comparisons of agricultural productivity growth in China and India. Journal of Productivity Analysis, 33, 209–223. Papola, T. S., & Sahu, P. P. (2012). Growth and structure of employment in India. New Delhi: Institute for Studies in Industrial Development. Pursell, G., Gulati, A., & Gupta, K. (2009). India in distortions to agricultural incentives in Asia. pp. (339–378) Washington, DC: The World Bank. Rajaraman, I. (2005). Taxing agriculture in a developing country: A possible approach. In B. H. Baltagi & E. Saddka (Eds.), Taxing the hard to tax: A possible approach (pp. 245–268). Emerald Group Publishing Unlimited. Ramakumar, R. (2010). Continuity and change: Notes on agriculture in ‘New India’. In A. D’Costa (Ed.), A New India? Reflections in the long twentieth century (pp. 43– 70). London and New York: Anthem Press. Ruttan, V. W., & Hayami, Y. (1998). Induced innovation model of agricultural development. In C. K. Eicher & J. M. Staatz (Eds.), International Agricultural Development (pp. 163–180). Baltimore: Johns Hopkins University Press. Shapiro, H., & Taylor, L. (1990). The state and industrial strategy. World Development, 18, 861–878.