Using a newly constructed panel dataset for agriculture in 17 OECD countries over the 1973–2011 period, we investigate the role of capital deepening in affecting agricultural TFP growth and the convergence of relative TFP levels across countries with different relative factor endowments. Our results show that capital deepening contributes positively to agricultural productivity growth among countries with similar levels of land relative to labor as reflected in relative prices. Depending on the relative endowments of land to labor, countries with relatively more abundant land are more likely to achieve technological gains through capital deepening than countries with relatively more labor. This finding is consistent with Hayami and Ruttan ( 1970a ) and provides supportive evidence for the induced innovation hypothesis.

This paper employs a stochastic frontier approach to examine how climate change and extreme weather affect U.S. agricultural productivity using 1940-1970 historical weather data (mean and variation) as the norm.We have four major findings.First, using temperature humidity index (THI) load and Oury index for the period 1960-2010 we find each state has experienced different patterns of climate change in the past half century, with some states incurring drier and warmer conditions than others.Second, the higher the THI load (more heat waves) and the lower the Oury index (much drier) will tend to lower a state's productivity.Third, the impacts of THI load shock and Oury index shock variables (deviations from historical norm fluctuations) on productivity are more robust than the level of THI and Oury index variables across specifications.Fourth, we project potential impacts of climate change and extreme weather on U.S. regional productivity based on the estimates.We find that the same degree changes in temperature or precipitation will have uneven impacts on regional productivities, with Delta, Northeast, and Southeast regions incurring much greater effects than other regions, using 2000-2010 as the reference period.

This paper uses panel data for the 1980-2004 period to estimate the contributions of public research to U.S. agricultural productivity growth. Local and social internal rates of return are estimated accounting for the effects of R&D spill-in, extension activities and road density. R&D spill-in proxies were constructed based on both geographic proximity and production profile to examine the sensitivity of the rates of return to these alternatives. We find that extension activities, road density, and R&D spill-ins, play an important role in enhancing the benefit of public R&D investments. We also find that the local internal rates of return, although high, have declined through time along with investments in extension, while the social rates have not. Yet, the social rates of return are not robust to the choice of spill-in proxy.

This paper provides a farm sector comparison of real values of capital input for 17 OECD countries for the period 1973-2011. The starting point for construction of a measure of capital input is the measurement of capital stock. Estimates of depreciable capital input are derived by representing capital stock at each point of time as a weighted sum of past investments. The capital stocks of land are measured as implicit quantities derived from balance sheet data. We convert estimates of capital stock into estimates of capital service flows by means of capital rental prices. Implicit rental prices for each asset are based on the correspondence between the purchase price of the asset and the discounted value of future service flows derived from that asset. Finally, comparisons of relative levels of capital input across countries require data on relative prices of capital input. We obtain relative prices of capital input via relative investment goods prices, taking into account the flow of capital input per unit of capital stock in each country.

It is widely reported that productivity growth is the main contributor to output growth in U.S. agriculture. This article provides estimates of output growth over the postwar period and decomposes that growth into the contributions of input growth and productivity growth. The analysis is based on recently revised production accounts for agriculture. Our findings are fully consistent with those reported in the literature. Productivity growth dominates input growth as a source of output growth in the sector.

This paper provides a farm sector comparison of relative levels of capital input for 17 OECD countries for the period 1973-2011, with an explicit distinction between land and depreciable assets. Methodologically, we adopt the constant efficiency model to derive capital services from capital stocks and construct the purchasing power parity between countries for crosscountry comparison. Our estimates show that, after accounting for cyclical fluctuation in the relative price of capital inputs, fifteen of the sixteen countries in the comparison had higher levels of capital input relative to the United States in 2011 than at the beginning of the sample period in 1973. Moreover, our analysis shows that increases in relative capital use on farms in OECD countries were accompanied by change in the structure of the capital input, away from land and towards depreciable capital items.

U.S. agricultural output more than doubled between 1948 and 2011, with growth averaging 1.49 percent per year. With little growth in total measured use of agricultural inputs, the extraordinary performance of the U.S. farm sector was driven mainly by increases in total factor productivity (TFP—measured as output per unit of aggregate input). Over the last six decades, the mix of agricultural inputs used shifted significantly, with increased use of intermediate goods (e.g., fertilizer and pesticides) and less use of labor and land. The output mix changed as well, with crop production growing faster than livestock production. Based on econometric analysis of updated (1948-2011) TFP data, this study finds no statistical evidence that longrun U.S. agricultural productivity has slowed over time. Model-based projections show that in the future, slow growth in research and development investments may have only minor effects on TFP growth over the next 10 years but will slow TFP growth much more over the long term.

This paper investigates the role of energy on U.S. agricultural productivity using panel data at the state level for the period 1960–2004. We first provide a historical account of energy use in U.S. agriculture. To do this we rely on the Bennet cost indicator to study how the price and volume components of energy costs have developed over time. We then proceed to analyze the contribution of energy to productivity in U.S. agriculture employing the Bennet–Bowley productivity indicator. An important feature of the Bennet–Bowley indicator is its direct association with the change in (normalized) profits. Thus our study is also able to analyze the link between profitability and productivity. Panel regression estimates indicate that energy prices have a negative effect on profitability in the U.S. agricultural sector. We also find that energy productivity has generally remained below total farm productivity following the 1973–1974 global energy crisis.

This paper presents revised procedures for calculating total factor productivity and measuring productivity growth in U.S. agriculture over the postwar years. Our estimates reflect (1) a disaggregated treatment of outputs and inputs and (2) indexing / procedures that do not im ose a priori restrictions on the structure of production. We find that productivity grew at the average annual rate of 1. 5 percent during the 1948-79 period, compared with the 1.70 percent per year estimated by the U.S. Department of Agriculture. The similar estimates of productivity growth overshadow some important differences in measurement of individual inputs.

A recent review of ERS’s productivity accounts recommended that ERS treat dairy cows, breeding beef cows and other long‐lived working animals as capital assets (Shumway, et. al 2014). BEA was also given the same recommendation in the international guidelines for national accounts, System of National Accounts 2008 (SNA 2008). In ERS’s farm accounts and BEA’s National Income and Product Accounts (NIPA’s), long‐lived working animals are currently treated as an inventory asset. This paper recalculates the farm accounts and NIPA’s when long‐lived working animals are re‐classified as a capital asset. We show that this reclassification raises farm output and GDP for every year – but the increase is larger for earlier years. As a result, real farm output growth and real GDP growth falls slightly when long‐lived working animals are capitalized. Total factor productivity (TFP) growth falls slightly from 1.42% per year to 1.38% per year when year when long‐lived working animals are capitalized.

This paper provides a farm sector comparison of relative levels of capital input for seventeen OECD countries for the period 1973-2011. The starting point for construction of a measure of capital input is the measurement of capital stock. Estimates of depreciable capital are derived by representing capital stock at each point of time as a weighted sum of past investments. The weights correspond to the relative efficiencies of capital goods of different ages, so that the weighted components of capital stock have the same efficiency. The capital stocks of land are measured as implicit quantities derived from balance sheet data. We convert estimates of capital stock into estimates of capital service flows by means of capital rental prices. Implicit rental prices for each asset are based on the correspondence between the purchase price of the asset and the discounted value of future service flows derived from that asset. Finally, comparisons of levels of capital input among countries require data on relative prices of capital input. We obtain relative price levels for capital input via relative investment goods prices, taking into account the flow of capital input per unit of capital stock in each country.

The U.S. population has more than doubled in the last six decades, as has agricultural output. U.S. agriculture now uses about 25 percent less farmland and 78 percent less labor than in 1948, so agricultural productivity is largely responsible for the increased production. Agricultural productivity can be defined in terms of total output per unit of a single input— partial factor productivity (PFP) measures such as land productivity (yield) and labor PRINT PDF EMAIL

This article provides a comparison of levels and growth of agricultural total factor productivity between Australia, Canada, and the United States for the 1961–2006 period. A production account for agriculture that is consistent across the three countries is constructed to estimate output, input and total factor productivity, and a dynamic panel regression is used to link the productivity estimates to potential determinants. We show that investment in public research and development and infrastructure plays an important role in explaining differences in productivity levels between countries. The findings provide useful insights into how public policy could be used to sustain agricultural productivity growth.

Recent studies that compare agricultural total factor productivity across countries use either the superlative index approach or the quantity-only based index approach, generating significantly different results. We demonstrate theoretically that the difference comes from measurement errors in implicit prices used by the quantity-only based index which differ significantly from market prices used by the superlative index. Using a novel dataset built upon a cross-country consistent production account for the United States, Canada and Australia, we show that the superlative index approach which uses both price and quantity information always outperforms the quantity-only based index approach which uses quantity information only, in terms of accuracy and consistency in aggregation. Our finding highlights the importance of collecting price data for performing international comparisons of agricultural productivity.

This study employs a Tὄrnqvist index approach to construct quality-adjusted labor index for the U.S. farm sector using the volume (hours worked) of 192 demographic components and their corresponding cost shares. We decompose labor input change into quality change and quantity change. The results show that between 1948 and 2011 the decline of total hours worked resulted in -0.58 percentage points of output growth per year while increasing labor quality contributed to 0.08 percentage points of annual output growth. We further decompose labor quality change into a change in the educational attainment of the labor force and a change due to other factors. Our results show that the education component contributed to most of the labor quality changes during the study period. However, the contribution of educational attainment is greater in earlier years than in later years.

1 背景 1990~2000年间,农作物产量增长速度放缓(图1),农作物实际价格经过长时间的衰退,在本世纪末迎来了增长.这些变化关系到美国农业是否能够在未来继续保持生产率的持续增长和可持续生产.美国是世界上最大的农产品消费国和生产国之一.随着全球人口数量和粮食需求量的逐步增加,美国是否能够继续保持生产率持续增长,不仅会影响美国的食品市场,同时也会威胁全球粮食安全.