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Technological choice of Chinese rice farmers
TECHNOLOGICAL
CHOICE OF
CHINESE RICE FARMERS Yiping Huang and K. P. Kalirajan
ABSTRACT: This paper investigates the technological choice followed in China’s rice production, using primary farm household survey data collected in 1994. Drawing on the modelling procedures used by Lin (1991). the empirical testing done in this paper fails to confirm the hypothesis of induced technological choice, the well known Hicks-Hayami-Ruttan-Binswanger hypothesis. The analysis reveals that Lin’s formulation may under certain circumstances lead to odd results when looking at cross section data. As an alternative specification, this study proposes cost shares in the place of physical quantities while modelling the production process. Empirical results using our suggested specification clearly confirm the hypothesis of induced technological choice. J.55: 033, Q12, Q/6
I. INTRODUCTION Drawing on Solow’s (1957) arguments, output growth may conventionally be decomposed into growth due to expansion of factor inputs and growth due to technological progress.’ The characteristics of agricultural production technologies can be generally classified into two categories-‘land-saving’ (Hayami and Ruttan, 1985) and ‘labour-saving’ (Binswanger and Ruttan, 1978). Land-saving technologies induce the liberal use of modem agricultural inputs such as chemical fertilisers to substitute for land, while labour-saving technologies to substitute other inputs for labour. Farmers operating in a market economy will be directed by changes in factor prices to search for technological alternatives to substitute for the increasingly scarce factor of production. Economies with different patterns of factor endowments usually choose different production technologies and have different paths of technological innovation. Hayami and Ruttan (1985) developed the theory of induced technological innovation in agriculture through international comparison of productivity growth and, in particular, comparison of alternative paths of technological development between Japan and the United States. In a recent study on China’s agriculture, Lin (1991) explores the patterns of technological choice in an economy with inhibited factor markets and confirms the Hicks-Hayami-Ruttan-Binswanger hypothesis. The objective of this paper is to examine the technological choice of the Chinese rice farmers in the post-reform period, using primary household survey data collected during 1994. The motivation for conducting this study includes the following. First, as Lin proves, if the central planners were rational in allocating land-saving and labour-saving technologies (in an effort to maximise national output, for instance), do individual farmers really Direct all correspondence to: Yiping Huang, Department Studies, Australian National University.
of Economics,
China Economic Review, Volume 7, Number 2, 1996, pages 181-191 All rights of reproduction in any form reserved.
Research School of Pacific and Asian
Copyright
0 1996 by JAI Press Inc. ISSN: 1043-951X.
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respond sensitively in the post-reform period when there is no factor market? One may argue that part of Lin’s evidence for the post-reform period production behaviour may be the consequence of the technological pattern followed before the reform (Wakashiro 1990).2 By 1994, however, the household responsibility system had already been adopted for more than 10 years and it should be possible to see farmers’ behaviour more clearly using recent survey data. Second, although the theories of induced technological choice evolved from micro-firm behaviour, earlier empirical work including that of Hayami and Ruttan (1985) and Lin (199 1) have used aggregated national or provincial data. The interesting question can be asked as whether there will be different results if micro-firm level disaggregated data are used. The availability of the recent farm household survey data facilitates such an experiement. Third, while Lin’s study looks at the agricultural sector as a whole, in this paper we are only interested in rice growers’ behaviour in China’s traditional grain producing regions. Since rice is an important commodity in the Chinese economy, state intervention in grain market has been heavier than in other agricultural markets and farmers also sometimes pursue self-sufficiency regardless of production cost. Thus, it is interesting to examine if rice farmers’ technological choice is induced by their factor endowments. The paper is organised as follows. The next section introduces the theory of induced technological choice in agriculture and reviews some earlier works. The third section discusses the data set and provides a preliminary test of the hypothesis using the farm household survey data. In the fourth section, an alternative formulation for the hypothesis testing, based on cost shares, is suggested and the hypothesis is tested again using the same data set. The last section summarises the paper.
II. THE HYPOTHESIS
OF INDUCED
TECHNOLOGICAL
CHOICE
The concept of induced innovation came mainly from the theory of the firm. Hicks (1932) suggested that a rise in the price of one factor relative to that of other factors induces a sequence of technical changes that reduce the use of that factor relative to the use of other factor inputs. It is also argued that in an economy, innovative efforts will be directed toward saving the relatively more expensive factors (Ahmad, 1966; Binswanger, 1974). In their celebrated study, Hayami and Ruttan (1985) analysed alternative paths of technical change and productivity growth in the agricultural sector of several countries, especially in the course of industrialisation. They introduced a useful concept of the metaproduction function which is regarded as an envelope of the commonly conceived neoclassical production functions. It is hypothesised that the adaptation of agriculture to new opportunities, arising from industrialisation involves a movement to a more efficient point on the metaproduction function.3 They suggested that, in extreme cases, the relative prices of land and labour may induce completely opposite paths of productivity growth. Comparing intercountry experiences, they concluded that the relative endowments of land and labour, at the time a nation enters into the development process, apparently have a significant influence upon the optimal path to be followed in moving along the metaproduction function. Where labour is the limiting factor, the optimum for new opportunities in the form of lower prices of modem inputs is likely to be along a path characterised by a higher land-labour ratio. In this context, movement towards an optimal position on the metaproduction function would involve development and adoption of new mechanical inputs. On the other hand, where land is the
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limiting factor, the new optimum is likely to be the point at which the yield per hectare is higher for the higher level of fertiliser input. Movement to this point would involve development and adoption of new biological and chemical inputs (Hayami and Ruttan, 1985). The above analysis by Hayami and Ruttan has important implications for alternative technological choices. Given the relative prices of land-saving and labour-saving technologies, the levels of application of the alternative technologies in countries or regions are determined by the relative prices of land and labour. Often, fertiliser use is regarded as a typical land-saving technology and tractor a typical labour-saving technology. In a crosssectional data set, we should be able to observe that producers facing high relative price of land to labour, use more fertilisers while those facing low relative price of land to labour, use more tractors for ploughing. In other words, the Hayami and Ruttan analysis leads directly to a hypothesis of induced technological choice: the relative price of land to labour is positively correlated with the use of land-saving technologies and negatively correlated with the use of labour-saving technologies.4 Relative prices of land and labour, however, are difficult to observe in economies where there is no free market for labour and, particularly, land. In this context, Lin (1991) poses the question whether or not farmers respond sensitively to the relative scarcity of land and labour in their technological choice when factor market exchanges are prohibited. He identified a model in which the markets for land-saving (I> and labour-saving (k) technologies are perfect. The farm is assumed to maximise its total output given its budget to buy the two types of technologies. Sketching the properties of the model, he arrives at the following implicit demand functions 1, = F(L,, Ki, Ai)
(1)
(-)(+) ki = G(L,, Ki, Ai)
(2)
(-)(+) where Ai is a set of variables relevant to farm i such as input and output prices, total income and some technological coefficients. The implicit demand functions (1) and (2) suggest that demand for labour-saving technology in a farm is negatively correlated with its labour force but positively correlated with its land area. The demand for land-saving technology has just the opposite signs of correlations with its factor endowments. Equations (1) and (2) were empirically tested by Lin, using China’s provincial data from 1970 to 1987. Lin (1991) argued that the increasing scarcity of one factor in agriculture, raises marginal returns to that factor and that it would induce farmers to search for new types of technologies that are substitutable for the concerned scarce factor. He concluded that, as long as the markets for technological inputs are not restricted, farmers’ technological choice under the prohibited factor markets is still consistent with the Hicks-HayamiRuttan-Binswanger hypothesis. III. THE DATA SET AND PRELIMINARY
TESTS
Lin’s formulation is applied here to test the hypothesis of induced technological choice, using China’s micro-level farm household data collected during 1994. The data set is drawn
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from a recent household survey of grain growers in China by the Ministry of Agriculture in China and the China Economic Research Unit at the University of Adelaide.’ The survey covers five traditional grain producing provinces: Jilin of Northeast China, Shangdong of East China, Jiangxi of central China, Sichuan of Southwest China and Guangdong of South China. While maize is the major grain crop in Jilin and wheat is the major grain crop in Shangdong, rice is the major grain crop in Jiangxi, Sichuan and Shangdong. To conduct the survey, 4 counties were chosen from each province, 10 villages from each county and 5 households from each village. The whole survey makes up a sample of 1,041 observations.6 The objective of this study is to examine whether Chinese grain growers respond sensitively to their relative factor endowments in their technological choices. The fact that farmers in different regions are involved in the production of different mix of crops may complicate the analysis of technological choices. We, therefore, restrict our analysis to examine the production behaviour of rice farmers. A subset of data concerning rice growers from Jiangxi, Sichuan and Guangdong provinces is constructed. All these provinces are in Southern China. By considering only the observations with valid and comparable entries, a sample of 602 observations were used to define a meta-production function for rice production.7 Following the literature on induced innovation, we define the level of fertiliser input in rice production as a land-saving technology (k) and the use of tractors for ploughing as a labour-saving technology (I). The household survey data contain very detailed information about quantities and values of different types of fertilisers applied in rice production. In this study, the physical quantities of fertiliser application are converted to net quantities of N, K20 and P,O, using the conversion ratios provided by the Ministry of Agriculture. The survey data also have information about hours of tractor use for ploughing and its costs. But tractor use hours were very poorly reported.* We, therefore, have to rely on the reports of costs of tractor ploughing. To obtain a rough idea about variations in physical quantities of tractor ploughing, we have to deflate the costs by the fertiliser price index for each household assuming that prices of fertiliser and tractor use moved in the same direction across households and regions.9 Drawing heavily on Lin (1991), the following empirical model has been used for testing the hypothesis of the characteristics of the choice of technologies in rice production in China: Z,.=
a0
+
a, Ki + ct2Lj + a3yi + cq,yc; + ct5pri
+
a,&.
ki = PO + PlKi + P&i + PRY; + PdYci + P,pr, + P&i
+
ef
+ a:
(3) (4)
in which regional dummies are omitted, and Ki is household i’s planting area for rice production (mu), Lj is inputs (working days), Yi is per capita income (Juan), yci is the share of crop income in household’s total income, pri is the average price of rice and pfi is average We recognise that the factor variables used on the right price of fertilisers (yuanlkg).” hand side of the equation are also their input levels instead of primary factor endowment. This was because when we look at rice production, one production activity, the households’ total factor endowments become irrelevant for farmers’ choice of production technology. Still, the variables used in Equations (3) and (4) provides good representation of the relative scarcity of factors in households’ rice production.’ I Two sets of (3) and (4) were estimated, using the dependent variable in both value terms and real terms. The former approach can be justified if prices of the technologies are iden-
185
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tical within each of the provinces. Otherwise, the latter approach can be followed by including provincial dummy variables in the regressions. If Chinese rice farmers’ technological choice is consistent with the Hicks-Hayami-Ruttan-Binswanger hypothesis, we would expect that
The survey data on China’s rice growers described above was used to estimate (3) and (4) applying the heteroscedasticity-consistent estimation method and the results are reported in Table 1. Columns (1) and (2) are results using the dependent variables in value terms while (3) and (4) refers to dependent variables in real terms. The empirical results do not confirm the hypothesis. In the two equations where dependent variables are in value terms, the land variable is not significant in the equation describing the demand for tractor ploughing.‘* Coefficient estimates of labour use in both equations are significant, but the coefficient has the wrong sign in the equation describing the demand for tractor ploughing. In the two equations where the dependent variables are in real terms, the results are similar. It seems that rice farmers’ decisions on demands for tractor ploughing and fertiliser use are uncorrelated with the households’ land areas (or the relative scarcity of rice land). More importantly, the demand for tractor ploughing is positively correlated with households’
Estimation
Table 1 Results: Levels of Application
of Tractor and Fertilisers
Inputs in Value Terms Tracror Ploughing
Dependent Variable Constant Planting areas Labour
Fertilser Applications
Inputs in Real Terms Tracror Ploughing
Fenilser Applicarions
(1)
(2)
(3)
(4)
-491.95***
-1572.80***
-410.62***
-298.70***
(4.3) 0.19 (0.03) 0.17*
(4.3) -37.82*
(4.3) 1.24
(4.3) -7.13
(0.3) 0.62*
(1.9) 1.10***
(2.0) 4.56***
Per capita income
(2.3) 110.27***
(3.9) 345.41***
(2.1) 99.73***
(4.3) 74.36***
Crop’s share in income
(4.8) 287.2 1***
(4.4) 1172.30***
(5.0) 285.18***
(4.5) 293.46***
Rice price
(3.2) 0.17
(3.8) -0.57
(3.4) 0.57
(4.4) 0.03
Fertiliser price
(0.6) 93.56
(0.6) 343.36
(1.1) 50.28
(0.2) 19.76*
(1.3)
(1.6)
(1.1)
(0.8)
-99.52
114.79
(1.8) 128.42*
(0.7) 418.18**
(2.3) 0.65
(2.4) 0.69
Regional dummies Jiangxi Sichuan R2 Notes:
The total number of observation r-ratios. Coeficients
with ***
the 5% level of significance.
-90.09***
(1.8) 71.22*
(1.5) 0.6 1
(2.0) 0.71
is 602. The numbers in parentheses under the estimated coeffkients
are significant
at the I% level of significance,
61.02
(1.7) 80.65
are the associated
** at the 2% level of significance
and * at
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labour use-the more the labour input is used in rice production, the higher is the demand for tractor use in ploughing. This result does not support the hypothesis concerning the choice of technology.
IV. AN ALTERNATIVE FORMULATION HYPOTHESIS TESTING
FOR
The grain sector has special characteristics in the Chinese agriculture. In the pre-reform China, the grain sector was strictly controlled by the Central Plans. Economic reform in the grain sector since 1979 has been has been impressive and also has produced mixed results. In 1994, state quotas for grain purchase still existed for most farmers and grain markets were still heavily restricted by the government. l3 The distortion in traditional grain producing regions are usually far more serious than in other regions. Not only are state purchase quotas for grain higher in these regions, but they also face more strict controls by the central and local governments. Continuous state intervention in grain markets reflects in part the government’s strong preference on basic self-sufficiency in grain.14 But theory emphasises that distortions in the product market would not significantly change farmer’s technological choice behaviour as long as they do not change farmers objective functions, If we compare the situation faced by rice producers in 1994 to that environment described in Lin (1991), we still find that many of Lin’s assumptions remain valid. Land circulation occurred in some areas but only accounted for a small proportion of total grain planting areas and exchange of land is still virtually prohibited. Labour flows occurred more widely and strongly. In many areas, farmers moved to the urban sector and to rural non-agricultural sectors. But this labour movement can still best be described as ‘limited mobility’. A huge amount of agricultural surplus labour still prevails, particularly in many traditional grain producing regions. The interesting question is: if Lin’s assumption are still valid in 1994, why do his formulation and modelling yield different results with farm-level household data? To answer this question, let us consider an example of two rice farmers A and B. It is assumed that their labour-land ratios are 1 for A and 10 for B (Table 2). Farmer A’s decision on fertiliser (10) and tractor ploughing (20) are fixed. We present two sets of choices for B. If B’s demand is 20 for fertiliser and 10 for tractor ploughing (Scenario l), we have, as expected,a negative correlation between fertiliser demand and labour-land ratio and a positive correlation between tractor demand and labour-land ratio. But if B’s demand is 60 for fertiliser and 30 for tractor, instead (Scenario 2), we have,as expected, a positive correlation between fertiliser demand and labour-land ratio. The correlation coefficient between tractor demand and labour-land ratio, however, has the wrong sign. Does this mean that farmer B acts irrationally? The answer is obviously not. In fact, his relative demands for fertiliser and tractor in the two scenarios are exactly the same (2:l) which is a rational response to his factor endowment, comparing to farmer A’s relative demand (1:2). There are several reasons for this outcome. One possibility concerns farmers’ budget for buying technologies. It is expected that the variation in this budget constraint is significant both across regions and across households. If a producer is an output maximiser, relaxation
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Table 2 Examples of Farmers’ Technological Scenurio
Labour-land ratio Fertiliser use Tractor plough
Choices Scenurio
I
2
A
B
A
B
1 10 20
10 20 10
1 10 20
10 60 30
in the budget constraint would push demands for the two inputs upward (before their marginal returns equal to zero). Again, if the farmer is rational, he would maintain a similar proportion between the two types of technologies. In the previous regression, although we included an income variable to proxy the impact of the budget constraint as suggested by Lin (1991), it probably failed to do so, because the relationship between income and the budget for rice production could vary tremendously from household to household. Another possibility is that because of the development of the non-agricultural sector, some farmers may gradually abandon their output maximisation behaviour and change to profit maximisation. Again, this step varies widely among households depending on non-agricultural opportunities available to them, on the degree of state intervention and on their confidence in food security. Therefore, we propose another formulation to test the hypothesis of induced technological choice. We use the cost share as the dependent variable. The advantage of this is that it avoids the complication created by different budget constraints and by differences in the objective functions relating to output and profit maximisation behaviours. As long as farmers are rational and respond sensitively to their relative scarcity of factors, they will keep a stable proportion between the levels of application of labour-saving and land-saving technologies. Based on the above argument, the following functions can be estimated to test the hypothesis sZi = a0 + alKi + a2Li + a3yi + a,yci
+ as&; + Ef
skj = PO + PIKi + PzLj + P3Yj + P4Ycj + PsPfi + ‘f where Sli is the cost share of fertiliser, ski is the cost share of tractor ploughing, both in percentage forms, and all the other variables are the same as those defined in equations (3) and (4). The variable of rice price included in the previous estimation is dropped here because it is not significant in explaining cost shares. The estimation results applying the heteroscedasticity-consistent method are reported in Table 3. Results in Table 3 support the hypothesis of induced technological choice. Although the adjusted R2 is not particularly high for both equations, all the estimates of key coefficients are significant at 0.01 significance level with the right signs. In the equation for tractor ploughing, its cost share is positively correlated with land areas for rice and negatively with labour input in rice production. The income level has a positive effect on the cost share of labour-saving technology. This is probably because a higher income level is usually associated with more non-grain employment and, therefore, lower labour input in grain production. The cost share for tractor use is also positively correlated with the fertiliser price. In the equation for fertiliser use, its cost share is negatively correlated with rice area and positively correlated with labour input. Income level has a negative impact on fertiliser
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ECONOMIC
Table 3 Results: Levels of Application
Estimation
REVIEW
(21 29.59*** (44.2) -0.13***
6.10***
68) 0.09***
Labour
(6.6) -0.01***
Per capita income
(3.3) 0.36***
(3.1) 0.02*** (5.3) -0.47***
(4.2)
(3.6)
Regional dummies Jiangxi
-4.41***
3.39***
Sichuan
(2.9) -6.55***
(2.8) 7.01***
R2
(4.3) 0.23
(6.1) 0.14
Notes:
The total number of observation r-ratios. Coefticients
with ***
is 602. The numbers in parentheses under the estimated
are significant
at the
I %levelof
1996
Cost Share of Fertiliser Input
/II
Planting areas
7(2)
of Tractor and Fertilisers
Cost Shrrre of Tructor Plough Constant
VOLUME
significance.
coefficients
are the associated
** at the 2% level of significance
and * at
the 5% level of significance. SOURY:
Authors’
estimation.
input and the explanation probably is the same as that offered for the tractor use equation. Surprisingly, fertiliser price is not significant in this equation. Across the region, we find that rice farmers in both Jiangxi and Sichuan provinces spent relatively more on fertilisers than those in Guangdong province. We therefore conclude that Chinese rice farmers’ technological choice is consistent with the Hicks-Hayami-Ruttan-Binswanger hypothesis, in spite of various forms of state intervention in the grain sector.
V. CONCLUSIONS This paper investigates the technological choice of Chinese rice farmers. The HicksHayami-Ruttan-Binswanger hypothesis is first tested within the modelling framework suggested by Lin (1991), using the farm household survey data of 1994. By using the dependent variables of fertiliser use and tractor ploughing, both in value and real terms, the empirical results failed to confirm the induced technological choice hypothesis. This finding, however, cannot lead to the conclusion that rice farmers in China are irrational. By providing an example, we argue that such odd results can occur even when all the farmers are responding sensitively to their relative scarcity of factors in the technological choice. There are several reasons for this outcome. One possibility is that the budget constraints vary significantly across households and another possibility is that the objective function is a mixture of output and profit maximisation behaviours. It is proposed that in testing the hypothesis of induced technological choice across households, cost shares instead of physical quantities should be used. Cost shares of labour-saving and land-saving technologies represent more clearly farmers’ response to relative prices of factors or relative scarcity of factors.
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Chinese Rice Farms
Empirical testing using the proposed modelling confirms that the technological Chinese rice farmers is induced by their relative scarcity of factors.
VARIABLES I
sl 1
sk L K Y YC Pr Pf
choice of
APPENDIX USED IN THE STUDY
Labour-saving technology. In this study it is refered to the tractor use for ploughing in rice production. The total cost on tractor ploughing (Juan) is directly drawn from the survey data. And this variable in real terms refers to the value term deflated by the fettiliser price. The share of cost on tractor use for ploughing in total production costs (W). Land-saving technology. In this study it is the level of fertiliser application in rice production. Total cost on tactor ploughing (Juan) is directly drawn from the survey data. The variable in real terms refers to the net quantity of N, K20 and P205 (kg) contained in fertilisers, calculated using conversion rations provided by China’s Ministry of Agriculture. The share of cost on fertilisers in total production costs (%). Total labour input used in rice production by the household (working day).
Total planting areas used for rice production (mu). Per capita income which is derived by dividing the household’s total income by its size Quadperson). Crop’s share in household’s total income. Average price of rice which is calculated by dividing the total income from rice by output Oluafig). Average price of fertiliser which is calculated by dividing the total cost on fertilisers by the net quantity of fertilisers (yuan/kg).
‘able Al Household Characteristics, Unit
Rice sample, observations = 522 Household head EDU qualitative DPRF dummy = 1 AT mu person POP RINCOME RHIRED Wheat sample, observations Household head
Mean
1994
St. Deviation
Minimum
Maximum
3.15 0.17 5.98
1.25 0.37 3.99
1.00 0.00 0.20
7.00 1.00 30.70
4.57 0.43 0.02
1.30 0.23 0.05
1.00 0.01 0.00
10.00
3.27 0.23 5.40 4.03 0.43 0.01
1.32 0.42 2.84 1.08 0.22 0.03
1.00 0.00 0.90 1.00 0.01 0.00
7.00 1.00 16.00 8.00 0.99 0.22
3.49 0.20 13.70 4.16 0.64 0.01
1.32 0.40 10.15 1.16 0.24 0.02
1.oo 0.00 0.00 2.00 0.00 0.00
7.00 1.00 52.00 8.00 1.00 0.15
1.00 0.53
= 522
EDU qualitative DPRF dummy AT mu person POP RINCOME RHIRED Maize sample, observations = 3.5 I Household head EDU qualitative DPRF dummy = 1 AT mu person POP RINCOME RHIRED
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NOTES The authors are grateful for helpful comments by Christian Bach, Colin Carter, Christopher Findlay and Terry Sicular. Financial support by the Australian Centre for International Agricultural Research is gratefully acknowledged. The third possible source of agricultural growth is to remove inefficiency in production or to reduce the distance between the level of actual output and the potential output. This is ignored here, though production inefficiency has been found to be an important issue in China’s agricultural production (Kalirajan et al. 1995). 2. Technological patterns, once followed, cannot be easily changed within a very short period. It is, for instance, difficult to sell a tractor, if there is no free market for tractors. 3. Hayami and Ruttan (1985) argue that it is rational for farmers in Japan, where prices of fertiliser are relatively low and prices of rice are relatively high, to plant varieties that are more responsive to high levels of fertilisation and to fertilise more heavily than farmers in Southeast Asia, where fertiliser prices are relatively higher than prices of rice. 4. While the interpretation of the hypothesis of induced technological choice formulated in this study different from the orginal Hayami and Ruttan hypothesis, we regard the former an extended version of the latter. 5. For a detailed discussion about the organisation of the survey and information contained in the data set, see Harry Wu, 1995, ‘Instruction manual for the database of the 1994 CERU/ MOA survey on China’s grain production and marketing’, Chinese Economy Research Unit, University of Adelaide, Adelaide. 6. In the sample, 201 households are from Jilin, 205 from Jiangxi, 215 from Guangdong, 200 from Sichuan and 220 from Shangdong. 7. Only a small proportion of farm households in Jilin and Shangdong provinces cultivates rice and these households are excluded from the subset of data used in this study. 8. A very large proportion of households did not respond to this question and the quality of the reported numbers of hours were bad. 9. We are of course fully aware of the weakness of this process. But no other information is available allowing us to deflate the costs of tractor ploughing appropriately. 10. We realise that it would be ideal to use prices at the margin rather than average, but marginal prices are not available in the data set. 11. For example, the relative price of labour may be high in relatively labour abundant households whose major of labour force is involved in non-agricultural activities. 12. The coefficient estimate of land in the fertiliser application equation is only significant at the 10% level of significance. 13. After the completion of the household responsibility system reform in 1983, the government introduced market mechanisms gradually for most agricultural products. The government also tried to reform its grain policy. The purchase of grain by the state, for instance, was changed into a contract system temporarily in 1985 in an attempt to marketise grain transactions. State quotas, however, were restored quickly after that. Another important reform step was taken in 1992 and, particularly, in 1993 when the state purchase prices and retail prices were brought to the same level. The dramatic fluctuation in grain market at the end of 1993 and rapid rise of grain prices in 1994 brought back many policy restriction measures to the grain sector (Huang 1995). 14. The most recent policy is that every province has to supply its own grain consumption. Due to the responsibility of maintaining regional self-sufficiency in grains and correlations between grain prices and local government budget, regional blocks to grain trade exist. Local markets for grain are segmented from one another. This reduces even farm households’ confidence in food security. It is frequently observed that those farmers obtaining non-agricul-
Chinese Rice Farms
tural jobs keep the contracted consumption.
191
land areas and produce
grains
at least for their own
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CHOICE OF
CHINESE RICE FARMERS Yiping Huang and K. P. Kalirajan
ABSTRACT: This paper investigates the technological choice followed in China’s rice production, using primary farm household survey data collected in 1994. Drawing on the modelling procedures used by Lin (1991). the empirical testing done in this paper fails to confirm the hypothesis of induced technological choice, the well known Hicks-Hayami-Ruttan-Binswanger hypothesis. The analysis reveals that Lin’s formulation may under certain circumstances lead to odd results when looking at cross section data. As an alternative specification, this study proposes cost shares in the place of physical quantities while modelling the production process. Empirical results using our suggested specification clearly confirm the hypothesis of induced technological choice. J.55: 033, Q12, Q/6
I. INTRODUCTION Drawing on Solow’s (1957) arguments, output growth may conventionally be decomposed into growth due to expansion of factor inputs and growth due to technological progress.’ The characteristics of agricultural production technologies can be generally classified into two categories-‘land-saving’ (Hayami and Ruttan, 1985) and ‘labour-saving’ (Binswanger and Ruttan, 1978). Land-saving technologies induce the liberal use of modem agricultural inputs such as chemical fertilisers to substitute for land, while labour-saving technologies to substitute other inputs for labour. Farmers operating in a market economy will be directed by changes in factor prices to search for technological alternatives to substitute for the increasingly scarce factor of production. Economies with different patterns of factor endowments usually choose different production technologies and have different paths of technological innovation. Hayami and Ruttan (1985) developed the theory of induced technological innovation in agriculture through international comparison of productivity growth and, in particular, comparison of alternative paths of technological development between Japan and the United States. In a recent study on China’s agriculture, Lin (1991) explores the patterns of technological choice in an economy with inhibited factor markets and confirms the Hicks-Hayami-Ruttan-Binswanger hypothesis. The objective of this paper is to examine the technological choice of the Chinese rice farmers in the post-reform period, using primary household survey data collected during 1994. The motivation for conducting this study includes the following. First, as Lin proves, if the central planners were rational in allocating land-saving and labour-saving technologies (in an effort to maximise national output, for instance), do individual farmers really Direct all correspondence to: Yiping Huang, Department Studies, Australian National University.
of Economics,
China Economic Review, Volume 7, Number 2, 1996, pages 181-191 All rights of reproduction in any form reserved.
Research School of Pacific and Asian
Copyright
0 1996 by JAI Press Inc. ISSN: 1043-951X.
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respond sensitively in the post-reform period when there is no factor market? One may argue that part of Lin’s evidence for the post-reform period production behaviour may be the consequence of the technological pattern followed before the reform (Wakashiro 1990).2 By 1994, however, the household responsibility system had already been adopted for more than 10 years and it should be possible to see farmers’ behaviour more clearly using recent survey data. Second, although the theories of induced technological choice evolved from micro-firm behaviour, earlier empirical work including that of Hayami and Ruttan (1985) and Lin (199 1) have used aggregated national or provincial data. The interesting question can be asked as whether there will be different results if micro-firm level disaggregated data are used. The availability of the recent farm household survey data facilitates such an experiement. Third, while Lin’s study looks at the agricultural sector as a whole, in this paper we are only interested in rice growers’ behaviour in China’s traditional grain producing regions. Since rice is an important commodity in the Chinese economy, state intervention in grain market has been heavier than in other agricultural markets and farmers also sometimes pursue self-sufficiency regardless of production cost. Thus, it is interesting to examine if rice farmers’ technological choice is induced by their factor endowments. The paper is organised as follows. The next section introduces the theory of induced technological choice in agriculture and reviews some earlier works. The third section discusses the data set and provides a preliminary test of the hypothesis using the farm household survey data. In the fourth section, an alternative formulation for the hypothesis testing, based on cost shares, is suggested and the hypothesis is tested again using the same data set. The last section summarises the paper.
II. THE HYPOTHESIS
OF INDUCED
TECHNOLOGICAL
CHOICE
The concept of induced innovation came mainly from the theory of the firm. Hicks (1932) suggested that a rise in the price of one factor relative to that of other factors induces a sequence of technical changes that reduce the use of that factor relative to the use of other factor inputs. It is also argued that in an economy, innovative efforts will be directed toward saving the relatively more expensive factors (Ahmad, 1966; Binswanger, 1974). In their celebrated study, Hayami and Ruttan (1985) analysed alternative paths of technical change and productivity growth in the agricultural sector of several countries, especially in the course of industrialisation. They introduced a useful concept of the metaproduction function which is regarded as an envelope of the commonly conceived neoclassical production functions. It is hypothesised that the adaptation of agriculture to new opportunities, arising from industrialisation involves a movement to a more efficient point on the metaproduction function.3 They suggested that, in extreme cases, the relative prices of land and labour may induce completely opposite paths of productivity growth. Comparing intercountry experiences, they concluded that the relative endowments of land and labour, at the time a nation enters into the development process, apparently have a significant influence upon the optimal path to be followed in moving along the metaproduction function. Where labour is the limiting factor, the optimum for new opportunities in the form of lower prices of modem inputs is likely to be along a path characterised by a higher land-labour ratio. In this context, movement towards an optimal position on the metaproduction function would involve development and adoption of new mechanical inputs. On the other hand, where land is the
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limiting factor, the new optimum is likely to be the point at which the yield per hectare is higher for the higher level of fertiliser input. Movement to this point would involve development and adoption of new biological and chemical inputs (Hayami and Ruttan, 1985). The above analysis by Hayami and Ruttan has important implications for alternative technological choices. Given the relative prices of land-saving and labour-saving technologies, the levels of application of the alternative technologies in countries or regions are determined by the relative prices of land and labour. Often, fertiliser use is regarded as a typical land-saving technology and tractor a typical labour-saving technology. In a crosssectional data set, we should be able to observe that producers facing high relative price of land to labour, use more fertilisers while those facing low relative price of land to labour, use more tractors for ploughing. In other words, the Hayami and Ruttan analysis leads directly to a hypothesis of induced technological choice: the relative price of land to labour is positively correlated with the use of land-saving technologies and negatively correlated with the use of labour-saving technologies.4 Relative prices of land and labour, however, are difficult to observe in economies where there is no free market for labour and, particularly, land. In this context, Lin (1991) poses the question whether or not farmers respond sensitively to the relative scarcity of land and labour in their technological choice when factor market exchanges are prohibited. He identified a model in which the markets for land-saving (I> and labour-saving (k) technologies are perfect. The farm is assumed to maximise its total output given its budget to buy the two types of technologies. Sketching the properties of the model, he arrives at the following implicit demand functions 1, = F(L,, Ki, Ai)
(1)
(-)(+) ki = G(L,, Ki, Ai)
(2)
(-)(+) where Ai is a set of variables relevant to farm i such as input and output prices, total income and some technological coefficients. The implicit demand functions (1) and (2) suggest that demand for labour-saving technology in a farm is negatively correlated with its labour force but positively correlated with its land area. The demand for land-saving technology has just the opposite signs of correlations with its factor endowments. Equations (1) and (2) were empirically tested by Lin, using China’s provincial data from 1970 to 1987. Lin (1991) argued that the increasing scarcity of one factor in agriculture, raises marginal returns to that factor and that it would induce farmers to search for new types of technologies that are substitutable for the concerned scarce factor. He concluded that, as long as the markets for technological inputs are not restricted, farmers’ technological choice under the prohibited factor markets is still consistent with the Hicks-HayamiRuttan-Binswanger hypothesis. III. THE DATA SET AND PRELIMINARY
TESTS
Lin’s formulation is applied here to test the hypothesis of induced technological choice, using China’s micro-level farm household data collected during 1994. The data set is drawn
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from a recent household survey of grain growers in China by the Ministry of Agriculture in China and the China Economic Research Unit at the University of Adelaide.’ The survey covers five traditional grain producing provinces: Jilin of Northeast China, Shangdong of East China, Jiangxi of central China, Sichuan of Southwest China and Guangdong of South China. While maize is the major grain crop in Jilin and wheat is the major grain crop in Shangdong, rice is the major grain crop in Jiangxi, Sichuan and Shangdong. To conduct the survey, 4 counties were chosen from each province, 10 villages from each county and 5 households from each village. The whole survey makes up a sample of 1,041 observations.6 The objective of this study is to examine whether Chinese grain growers respond sensitively to their relative factor endowments in their technological choices. The fact that farmers in different regions are involved in the production of different mix of crops may complicate the analysis of technological choices. We, therefore, restrict our analysis to examine the production behaviour of rice farmers. A subset of data concerning rice growers from Jiangxi, Sichuan and Guangdong provinces is constructed. All these provinces are in Southern China. By considering only the observations with valid and comparable entries, a sample of 602 observations were used to define a meta-production function for rice production.7 Following the literature on induced innovation, we define the level of fertiliser input in rice production as a land-saving technology (k) and the use of tractors for ploughing as a labour-saving technology (I). The household survey data contain very detailed information about quantities and values of different types of fertilisers applied in rice production. In this study, the physical quantities of fertiliser application are converted to net quantities of N, K20 and P,O, using the conversion ratios provided by the Ministry of Agriculture. The survey data also have information about hours of tractor use for ploughing and its costs. But tractor use hours were very poorly reported.* We, therefore, have to rely on the reports of costs of tractor ploughing. To obtain a rough idea about variations in physical quantities of tractor ploughing, we have to deflate the costs by the fertiliser price index for each household assuming that prices of fertiliser and tractor use moved in the same direction across households and regions.9 Drawing heavily on Lin (1991), the following empirical model has been used for testing the hypothesis of the characteristics of the choice of technologies in rice production in China: Z,.=
a0
+
a, Ki + ct2Lj + a3yi + cq,yc; + ct5pri
+
a,&.
ki = PO + PlKi + P&i + PRY; + PdYci + P,pr, + P&i
+
ef
+ a:
(3) (4)
in which regional dummies are omitted, and Ki is household i’s planting area for rice production (mu), Lj is inputs (working days), Yi is per capita income (Juan), yci is the share of crop income in household’s total income, pri is the average price of rice and pfi is average We recognise that the factor variables used on the right price of fertilisers (yuanlkg).” hand side of the equation are also their input levels instead of primary factor endowment. This was because when we look at rice production, one production activity, the households’ total factor endowments become irrelevant for farmers’ choice of production technology. Still, the variables used in Equations (3) and (4) provides good representation of the relative scarcity of factors in households’ rice production.’ I Two sets of (3) and (4) were estimated, using the dependent variable in both value terms and real terms. The former approach can be justified if prices of the technologies are iden-
185
Chinese Rice Farms
tical within each of the provinces. Otherwise, the latter approach can be followed by including provincial dummy variables in the regressions. If Chinese rice farmers’ technological choice is consistent with the Hicks-Hayami-Ruttan-Binswanger hypothesis, we would expect that
The survey data on China’s rice growers described above was used to estimate (3) and (4) applying the heteroscedasticity-consistent estimation method and the results are reported in Table 1. Columns (1) and (2) are results using the dependent variables in value terms while (3) and (4) refers to dependent variables in real terms. The empirical results do not confirm the hypothesis. In the two equations where dependent variables are in value terms, the land variable is not significant in the equation describing the demand for tractor ploughing.‘* Coefficient estimates of labour use in both equations are significant, but the coefficient has the wrong sign in the equation describing the demand for tractor ploughing. In the two equations where the dependent variables are in real terms, the results are similar. It seems that rice farmers’ decisions on demands for tractor ploughing and fertiliser use are uncorrelated with the households’ land areas (or the relative scarcity of rice land). More importantly, the demand for tractor ploughing is positively correlated with households’
Estimation
Table 1 Results: Levels of Application
of Tractor and Fertilisers
Inputs in Value Terms Tracror Ploughing
Dependent Variable Constant Planting areas Labour
Fertilser Applications
Inputs in Real Terms Tracror Ploughing
Fenilser Applicarions
(1)
(2)
(3)
(4)
-491.95***
-1572.80***
-410.62***
-298.70***
(4.3) 0.19 (0.03) 0.17*
(4.3) -37.82*
(4.3) 1.24
(4.3) -7.13
(0.3) 0.62*
(1.9) 1.10***
(2.0) 4.56***
Per capita income
(2.3) 110.27***
(3.9) 345.41***
(2.1) 99.73***
(4.3) 74.36***
Crop’s share in income
(4.8) 287.2 1***
(4.4) 1172.30***
(5.0) 285.18***
(4.5) 293.46***
Rice price
(3.2) 0.17
(3.8) -0.57
(3.4) 0.57
(4.4) 0.03
Fertiliser price
(0.6) 93.56
(0.6) 343.36
(1.1) 50.28
(0.2) 19.76*
(1.3)
(1.6)
(1.1)
(0.8)
-99.52
114.79
(1.8) 128.42*
(0.7) 418.18**
(2.3) 0.65
(2.4) 0.69
Regional dummies Jiangxi Sichuan R2 Notes:
The total number of observation r-ratios. Coeficients
with ***
the 5% level of significance.
-90.09***
(1.8) 71.22*
(1.5) 0.6 1
(2.0) 0.71
is 602. The numbers in parentheses under the estimated coeffkients
are significant
at the I% level of significance,
61.02
(1.7) 80.65
are the associated
** at the 2% level of significance
and * at
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labour use-the more the labour input is used in rice production, the higher is the demand for tractor use in ploughing. This result does not support the hypothesis concerning the choice of technology.
IV. AN ALTERNATIVE FORMULATION HYPOTHESIS TESTING
FOR
The grain sector has special characteristics in the Chinese agriculture. In the pre-reform China, the grain sector was strictly controlled by the Central Plans. Economic reform in the grain sector since 1979 has been has been impressive and also has produced mixed results. In 1994, state quotas for grain purchase still existed for most farmers and grain markets were still heavily restricted by the government. l3 The distortion in traditional grain producing regions are usually far more serious than in other regions. Not only are state purchase quotas for grain higher in these regions, but they also face more strict controls by the central and local governments. Continuous state intervention in grain markets reflects in part the government’s strong preference on basic self-sufficiency in grain.14 But theory emphasises that distortions in the product market would not significantly change farmer’s technological choice behaviour as long as they do not change farmers objective functions, If we compare the situation faced by rice producers in 1994 to that environment described in Lin (1991), we still find that many of Lin’s assumptions remain valid. Land circulation occurred in some areas but only accounted for a small proportion of total grain planting areas and exchange of land is still virtually prohibited. Labour flows occurred more widely and strongly. In many areas, farmers moved to the urban sector and to rural non-agricultural sectors. But this labour movement can still best be described as ‘limited mobility’. A huge amount of agricultural surplus labour still prevails, particularly in many traditional grain producing regions. The interesting question is: if Lin’s assumption are still valid in 1994, why do his formulation and modelling yield different results with farm-level household data? To answer this question, let us consider an example of two rice farmers A and B. It is assumed that their labour-land ratios are 1 for A and 10 for B (Table 2). Farmer A’s decision on fertiliser (10) and tractor ploughing (20) are fixed. We present two sets of choices for B. If B’s demand is 20 for fertiliser and 10 for tractor ploughing (Scenario l), we have, as expected,a negative correlation between fertiliser demand and labour-land ratio and a positive correlation between tractor demand and labour-land ratio. But if B’s demand is 60 for fertiliser and 30 for tractor, instead (Scenario 2), we have,as expected, a positive correlation between fertiliser demand and labour-land ratio. The correlation coefficient between tractor demand and labour-land ratio, however, has the wrong sign. Does this mean that farmer B acts irrationally? The answer is obviously not. In fact, his relative demands for fertiliser and tractor in the two scenarios are exactly the same (2:l) which is a rational response to his factor endowment, comparing to farmer A’s relative demand (1:2). There are several reasons for this outcome. One possibility concerns farmers’ budget for buying technologies. It is expected that the variation in this budget constraint is significant both across regions and across households. If a producer is an output maximiser, relaxation
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Table 2 Examples of Farmers’ Technological Scenurio
Labour-land ratio Fertiliser use Tractor plough
Choices Scenurio
I
2
A
B
A
B
1 10 20
10 20 10
1 10 20
10 60 30
in the budget constraint would push demands for the two inputs upward (before their marginal returns equal to zero). Again, if the farmer is rational, he would maintain a similar proportion between the two types of technologies. In the previous regression, although we included an income variable to proxy the impact of the budget constraint as suggested by Lin (1991), it probably failed to do so, because the relationship between income and the budget for rice production could vary tremendously from household to household. Another possibility is that because of the development of the non-agricultural sector, some farmers may gradually abandon their output maximisation behaviour and change to profit maximisation. Again, this step varies widely among households depending on non-agricultural opportunities available to them, on the degree of state intervention and on their confidence in food security. Therefore, we propose another formulation to test the hypothesis of induced technological choice. We use the cost share as the dependent variable. The advantage of this is that it avoids the complication created by different budget constraints and by differences in the objective functions relating to output and profit maximisation behaviours. As long as farmers are rational and respond sensitively to their relative scarcity of factors, they will keep a stable proportion between the levels of application of labour-saving and land-saving technologies. Based on the above argument, the following functions can be estimated to test the hypothesis sZi = a0 + alKi + a2Li + a3yi + a,yci
+ as&; + Ef
skj = PO + PIKi + PzLj + P3Yj + P4Ycj + PsPfi + ‘f where Sli is the cost share of fertiliser, ski is the cost share of tractor ploughing, both in percentage forms, and all the other variables are the same as those defined in equations (3) and (4). The variable of rice price included in the previous estimation is dropped here because it is not significant in explaining cost shares. The estimation results applying the heteroscedasticity-consistent method are reported in Table 3. Results in Table 3 support the hypothesis of induced technological choice. Although the adjusted R2 is not particularly high for both equations, all the estimates of key coefficients are significant at 0.01 significance level with the right signs. In the equation for tractor ploughing, its cost share is positively correlated with land areas for rice and negatively with labour input in rice production. The income level has a positive effect on the cost share of labour-saving technology. This is probably because a higher income level is usually associated with more non-grain employment and, therefore, lower labour input in grain production. The cost share for tractor use is also positively correlated with the fertiliser price. In the equation for fertiliser use, its cost share is negatively correlated with rice area and positively correlated with labour input. Income level has a negative impact on fertiliser
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ECONOMIC
Table 3 Results: Levels of Application
Estimation
REVIEW
(21 29.59*** (44.2) -0.13***
6.10***
68) 0.09***
Labour
(6.6) -0.01***
Per capita income
(3.3) 0.36***
(3.1) 0.02*** (5.3) -0.47***
(4.2)
(3.6)
Regional dummies Jiangxi
-4.41***
3.39***
Sichuan
(2.9) -6.55***
(2.8) 7.01***
R2
(4.3) 0.23
(6.1) 0.14
Notes:
The total number of observation r-ratios. Coefticients
with ***
is 602. The numbers in parentheses under the estimated
are significant
at the
I %levelof
1996
Cost Share of Fertiliser Input
/II
Planting areas
7(2)
of Tractor and Fertilisers
Cost Shrrre of Tructor Plough Constant
VOLUME
significance.
coefficients
are the associated
** at the 2% level of significance
and * at
the 5% level of significance. SOURY:
Authors’
estimation.
input and the explanation probably is the same as that offered for the tractor use equation. Surprisingly, fertiliser price is not significant in this equation. Across the region, we find that rice farmers in both Jiangxi and Sichuan provinces spent relatively more on fertilisers than those in Guangdong province. We therefore conclude that Chinese rice farmers’ technological choice is consistent with the Hicks-Hayami-Ruttan-Binswanger hypothesis, in spite of various forms of state intervention in the grain sector.
V. CONCLUSIONS This paper investigates the technological choice of Chinese rice farmers. The HicksHayami-Ruttan-Binswanger hypothesis is first tested within the modelling framework suggested by Lin (1991), using the farm household survey data of 1994. By using the dependent variables of fertiliser use and tractor ploughing, both in value and real terms, the empirical results failed to confirm the induced technological choice hypothesis. This finding, however, cannot lead to the conclusion that rice farmers in China are irrational. By providing an example, we argue that such odd results can occur even when all the farmers are responding sensitively to their relative scarcity of factors in the technological choice. There are several reasons for this outcome. One possibility is that the budget constraints vary significantly across households and another possibility is that the objective function is a mixture of output and profit maximisation behaviours. It is proposed that in testing the hypothesis of induced technological choice across households, cost shares instead of physical quantities should be used. Cost shares of labour-saving and land-saving technologies represent more clearly farmers’ response to relative prices of factors or relative scarcity of factors.
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Chinese Rice Farms
Empirical testing using the proposed modelling confirms that the technological Chinese rice farmers is induced by their relative scarcity of factors.
VARIABLES I
sl 1
sk L K Y YC Pr Pf
choice of
APPENDIX USED IN THE STUDY
Labour-saving technology. In this study it is refered to the tractor use for ploughing in rice production. The total cost on tractor ploughing (Juan) is directly drawn from the survey data. And this variable in real terms refers to the value term deflated by the fettiliser price. The share of cost on tractor use for ploughing in total production costs (W). Land-saving technology. In this study it is the level of fertiliser application in rice production. Total cost on tactor ploughing (Juan) is directly drawn from the survey data. The variable in real terms refers to the net quantity of N, K20 and P205 (kg) contained in fertilisers, calculated using conversion rations provided by China’s Ministry of Agriculture. The share of cost on fertilisers in total production costs (%). Total labour input used in rice production by the household (working day).
Total planting areas used for rice production (mu). Per capita income which is derived by dividing the household’s total income by its size Quadperson). Crop’s share in household’s total income. Average price of rice which is calculated by dividing the total income from rice by output Oluafig). Average price of fertiliser which is calculated by dividing the total cost on fertilisers by the net quantity of fertilisers (yuan/kg).
‘able Al Household Characteristics, Unit
Rice sample, observations = 522 Household head EDU qualitative DPRF dummy = 1 AT mu person POP RINCOME RHIRED Wheat sample, observations Household head
Mean
1994
St. Deviation
Minimum
Maximum
3.15 0.17 5.98
1.25 0.37 3.99
1.00 0.00 0.20
7.00 1.00 30.70
4.57 0.43 0.02
1.30 0.23 0.05
1.00 0.01 0.00
10.00
3.27 0.23 5.40 4.03 0.43 0.01
1.32 0.42 2.84 1.08 0.22 0.03
1.00 0.00 0.90 1.00 0.01 0.00
7.00 1.00 16.00 8.00 0.99 0.22
3.49 0.20 13.70 4.16 0.64 0.01
1.32 0.40 10.15 1.16 0.24 0.02
1.oo 0.00 0.00 2.00 0.00 0.00
7.00 1.00 52.00 8.00 1.00 0.15
1.00 0.53
= 522
EDU qualitative DPRF dummy AT mu person POP RINCOME RHIRED Maize sample, observations = 3.5 I Household head EDU qualitative DPRF dummy = 1 AT mu person POP RINCOME RHIRED
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NOTES The authors are grateful for helpful comments by Christian Bach, Colin Carter, Christopher Findlay and Terry Sicular. Financial support by the Australian Centre for International Agricultural Research is gratefully acknowledged. The third possible source of agricultural growth is to remove inefficiency in production or to reduce the distance between the level of actual output and the potential output. This is ignored here, though production inefficiency has been found to be an important issue in China’s agricultural production (Kalirajan et al. 1995). 2. Technological patterns, once followed, cannot be easily changed within a very short period. It is, for instance, difficult to sell a tractor, if there is no free market for tractors. 3. Hayami and Ruttan (1985) argue that it is rational for farmers in Japan, where prices of fertiliser are relatively low and prices of rice are relatively high, to plant varieties that are more responsive to high levels of fertilisation and to fertilise more heavily than farmers in Southeast Asia, where fertiliser prices are relatively higher than prices of rice. 4. While the interpretation of the hypothesis of induced technological choice formulated in this study different from the orginal Hayami and Ruttan hypothesis, we regard the former an extended version of the latter. 5. For a detailed discussion about the organisation of the survey and information contained in the data set, see Harry Wu, 1995, ‘Instruction manual for the database of the 1994 CERU/ MOA survey on China’s grain production and marketing’, Chinese Economy Research Unit, University of Adelaide, Adelaide. 6. In the sample, 201 households are from Jilin, 205 from Jiangxi, 215 from Guangdong, 200 from Sichuan and 220 from Shangdong. 7. Only a small proportion of farm households in Jilin and Shangdong provinces cultivates rice and these households are excluded from the subset of data used in this study. 8. A very large proportion of households did not respond to this question and the quality of the reported numbers of hours were bad. 9. We are of course fully aware of the weakness of this process. But no other information is available allowing us to deflate the costs of tractor ploughing appropriately. 10. We realise that it would be ideal to use prices at the margin rather than average, but marginal prices are not available in the data set. 11. For example, the relative price of labour may be high in relatively labour abundant households whose major of labour force is involved in non-agricultural activities. 12. The coefficient estimate of land in the fertiliser application equation is only significant at the 10% level of significance. 13. After the completion of the household responsibility system reform in 1983, the government introduced market mechanisms gradually for most agricultural products. The government also tried to reform its grain policy. The purchase of grain by the state, for instance, was changed into a contract system temporarily in 1985 in an attempt to marketise grain transactions. State quotas, however, were restored quickly after that. Another important reform step was taken in 1992 and, particularly, in 1993 when the state purchase prices and retail prices were brought to the same level. The dramatic fluctuation in grain market at the end of 1993 and rapid rise of grain prices in 1994 brought back many policy restriction measures to the grain sector (Huang 1995). 14. The most recent policy is that every province has to supply its own grain consumption. Due to the responsibility of maintaining regional self-sufficiency in grains and correlations between grain prices and local government budget, regional blocks to grain trade exist. Local markets for grain are segmented from one another. This reduces even farm households’ confidence in food security. It is frequently observed that those farmers obtaining non-agricul-
Chinese Rice Farms
tural jobs keep the contracted consumption.
191
land areas and produce
grains
at least for their own
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