2010年-世界发展银行全球_Measures_of_Fixed_Capital_in_Agriculture_39页_773kb

Summary of "Measures of Fixed Capital in Agriculture"

Core Content

This paper introduces a new data series on agricultural fixed capital, developed using a consistent methodology to allow for cross-country and cross-time comparisons. It challenges the common practice of using tractors as a proxy for agricultural fixed capital and instead constructs more comprehensive measures that include livestock and tree stock. The authors examine the evolution of agricultural capital from 1970 to 2000, highlighting the changing composition of capital and differences in capital accumulation across income groups.

Main Points

• Agricultural Capital Importance: Capital is a fundamental component of agricultural production, and its accumulation is crucial for growth and development.
• Data Series Construction: The paper constructs a new data series on agricultural fixed capital, including three sub-components: fixed capital, livestock, and treestock.
• Methodology: A modified perpetual inventory method is used to estimate capital stocks, incorporating depreciation and efficiency over time.
• Comparison with FAO Data: The new data series differs significantly from the FAO's tractor data, which is a partial and often misleading proxy for agricultural capital.
• Capital Composition Changes: There is a noticeable shift in the composition of agricultural capital, with livestock becoming less dominant and treestock and fixed capital increasing in importance.
• Income Group Differences: High-income countries show different capital accumulation patterns compared to middle- and lower-income countries, with the latter experiencing faster growth in treestock and fixed capital.
• Productivity Analysis: The authors use the new capital measures in productivity analyses, showing that input elasticities differ significantly from previous studies due to the improved data and methodology.
• State Variables: The paper incorporates state variables such as technology, institutions, and incentives to better understand the determinants of agricultural productivity.

Key Information

Fixed Capital

• Definition: Fixed capital includes structures, equipment, and machinery.
• Methodology: The perpetual inventory method is modified to account for depreciation and efficiency over time.
• Equation: The efficiency of an asset is modeled as a function of its age and lifetime, with the formula:
  $$
  s_j = \frac{L - j}{L - \beta j}, \quad 0 \leq j < L
  $$
  where $L$ is the lifetime of the capital good and $\beta$ is a curvature parameter.
• Data Sources: Data on fixed capital is obtained from national accounts, and the series is valued in constant (1990) US dollars using GDP deflators.

Livestock Capital

• Definition: Livestock includes animals used for breeding and draft power.
• Data Sources: FAO reports on farm animal quantities are used to calculate livestock capital.
• Valuation: Regional export unit values are used to value domestic herds, and the data is converted to constant (1990) dollars using the U.S. agricultural GDP deflator.

Treestock Capital

• Definition: Treestock includes orchards, plantations, and smallholder trees.
• Methodology: The present value of future income is calculated based on the area planted and expected prices.
• Assumptions: The authors assume production costs account for 80% of gross revenues and use a five-year moving average of producer prices to estimate expected income.

Data Coverage

• Countries Included: Australia, Austria, Canada, Cyprus, Denmark, Egypt, Finland, France, Greece, India, Indonesia, Italy, Kenya, Republic of Korea, Malawi, Mauritius, Morocco, the Netherlands, Norway, Pakistan, Peru, the Philippines, Sri Lanka, Sweden, Republic of Tanzania, Tunisia, Turkey, United Kingdom, United States, and Uruguay.
• Time Period: The data series for fixed capital begins in the 1960s, while livestock and treestock data starts in 1961.

Capital Growth Patterns

• Overall Growth: All countries showed positive capital accumulation since 1970.
• Median Growth Rates:
  • Fixed capital: 5.6%
  • Treestock: 5.7%
  • Livestock: 3.6%
• Decade Growth Rates:
  • 1970s: Fixed capital grew at 7.3%, Livestock at 3.9%, Treestock at 3.2%
  • 1980s: Fixed capital grew at 5.6%, Livestock at 4.0%, Treestock at 6.6%
  • 1990s: Fixed capital grew at 3.6%, Livestock at 3.8%, Treestock at 4.0%

Cross-Country Variability

• High-Income vs. Middle/Lower-Income Countries:
  • High-income countries: Fixed capital growth at 6.2%, Livestock at 3.3%, Treestock at 4.0%
  • Middle/Lower-income countries: Fixed capital growth at 5.5%, Livestock at 3.8%, Treestock at 6.6%

Comparison with Tractor Data

• Correlation: The correlation between tractor data and agricultural fixed capital data is moderate, with an average of 0.43 and a median of 0.8.
• Limitations: Tractor data is a partial measure, not including buildings, irrigation, or varying tractor quality and horsepower.

Agricultural Production Function

• Model: The production function is estimated as:
  $$
  y_{it} = x_{it} \beta(s) + s_{it} \gamma + m_{0it} + u_{0it}
  $$
• State Variables: Include technology, institutions, and incentives, which are used to explain variations in productivity.
• Technology Variables:
  • Human capital (schooling years of labor force)
  • Peak yield (Paasche index based on commodity yields and land area)
  • Development indicator (infrastructure, public health, research, institutions)
• Institutional Variables:
  • Political rights (electoral process, pluralism, government function)
  • Civil liberties (freedom of expression, rule of law, personal autonomy)
• Incentive Variables:
  • Relative prices (terms of trade between agriculture and the overall economy)
  • Price variability (market risk)
  • Inflation (economy-wide market risk)

Conclusion

The paper emphasizes the importance of accurate and comprehensive measures of agricultural capital for empirical productivity analysis. It highlights the limitations of using tractors as a proxy and introduces a more robust data series that includes livestock and treestock. The new data reveals significant differences in capital composition and accumulation across countries and income groups, providing a more nuanced understanding of agricultural growth and productivity.