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The purpose of this paper is to investigate the endogeneity of asset values and how it relates to farm financial stress in US agriculture. The authors conceptualize an implied measure of farm financial stress as a function of debt position. The authors posit that there are variations in the asset values that are beyond the farmer’s control and therefore have implications on farm debt.

The framework recognizes the endogeneity of return on assets (ROA). It uses a non-parametric technique to approximate the variance of expected ROA (VEROA). The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Further, the authors use a dynamic balanced panel data set from 1960 to 2011 for 15 US agricultural states from the Agricultural Resource Management Survey, and information from traditional state-level financial statements.

Estimation of linear dynamic debt panel data models accounting for the endogeneity of ROA and VEROA is a challenging task. Estimated variances are unstable. Hence, the authors focus on variance specification that uses the residuals squared from the ARIMA specification and non-parametric estimators. Arellano-Bover/Blundell-Bond generalized method of moments estimation procedures, although may be biased, show that VEROA has a negative and significant effect on the total amount of debt in the agricultural sector.

The instruments used in this analysis are lagged regressors which may be weakly correlated with the relevant first-order condition, hence not properly identifying the parameters of interest. Future research could include the identification of better instruments, potentially use of sequential moment conditions.

Unlike previous study, the authors use non-parametric approximation of VEROA. The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Second, the authors make use of a large dynamic balanced panel data set from 1960 to 2011 for 15 agricultural states in the USA. To the best of the authors’ knowledge, this study is one of the few that provides evidence on risk-balancing behavior at the agricultural sector level, of the USA.

The lack of theoretical and pragmatic way of measuring agricultural commercialization has been responsible for the inconsistent results for the impact of agricultural commercialization on household welfare. This study makes use of an input-based market participation approach that utilizes household preplanting production decision to stratify farming households according to production orientation.

The study estimates a system of input and consumer demand equations. It augments traditional input and consumer demand equations with an additional variable based on an endogenous switch, which measures the probability of being a commercial farming household. Empirical evidence suggests that market orientation is an important determinant of the level of traded input and hence, market participation. Predicted probabilities obtained from the endogenous switch are used to stratify households into subsistence and commercial agricultural households.

Results of the relative effect of commercial agriculture on the level of household food security support the claim that production orientation does affect the relationship between the relative share of food expenditure to the household total expenditures and the logarithm of household expenditure for this part of sub-Saharan Africa.

As in the case of all generalized method of moments studies, the results depend on the robustness of the instruments. However, search for better instruments may run afoul of Leamer's ad hoc specification search with nonexperimental data.

This paper is original in its formulation of an endogenous switch between subsistence and commercial agriculture. This switch is estimated as a latent variable following a logit form.

The purpose of this research is to analyze possible implications of the economic measures presented in the balance sheet and income statement of the farm firm.

Accounting principles and the users of accounting information are studied. From a review of the Agricultural Resource Management Survey (ARMS) questionnaire, several items are identified that limit ARMS information from fully measuring economic and financial conditions.

ARMS limitations include issues related to asset valuation, income and expense recognition, and extraordinary income reporting. In particular, data limitations on deferred taxes associated with market values exceeding cost, capital leases, prepaid rents, accrued items, Section 179 and accelerated depreciation methods, and extraordinary items may result in understatement of leverage, overstatement of liquidity, and under reporting of year‐to‐year farm income variability measures.

By identifying these limitations, changes can be made that may result in improved measures of farm financial condition and farm household well‐being.

Over the past four decades, real values of farm real estate and the share of assets on farmers’ balance sheets attributed to farm real estate have increased. The purpose of this paper is to examine the factors that explain the concentration of the US agricultural balance sheet around a particular asset, farm real estate, and the extent to which the degree of asset concentration varies across United States Department of Agriculture production regions.

State-level data from 48 states and entropy-based inequality measures are used to examine changes in asset distributions (real estate vs non-real estate assets) both within and between regions over time.

The agricultural balance sheet is found to concentrate into real estate in the USA over the period 1960-2003 with the rate of concentration varying across production regions. In some regions, the concentration is mainly due to changes in real estate prices, while in other regions concentration is also driven by changes in real estate holdings or changes in total factor productivity.

This study formally estimates the degree to which the concentration of balance sheet items can be explained by the observed changes in farm real estate prices relative to observed changes in agricultural factor productivity or changes in farm real estate holdings. The computed regional differences in asset concentration and its main drivers have implications for changes in equity and solvency positions of farmers as well as agricultural lenders’ risk exposure.

The purpose of this research is to examine the usability and communication methods of the Agricultural Resource Management Survey (ARMS) data. Recommendations for improving access and usability are proposed to Economic Research Service (ERS).

The current methods for accessing the ARMS data are described. Several accounting issues related to the usability of the data are presented. Cost of production issues related to the data are also discussed.

Recommendations to ERS include: increase efforts to disseminate the ARMS results more widely, make the ARMS web tool easier to access, develop partnerships with universities, increase the value of the web tool by providing more information on the data that are already available, consider the accounting items of extraordinary income, inventory valuations, and nonmonetary income and consider issues related to cost of production items.

By identifying the factors limiting the current use of the ARMS data, changes can be made that may result in wider dissemination and use of the data.

The purpose of this research is to examine the effect of accounting for complex organizational forms on data collection with the Agricultural Resource Management Survey (ARMS).

This research reviews the literature from accounting theory along with the goals of data collection for policy analysis to draw conclusions about the applicability of accounting pronouncements.

Historically, the financial data collected in ARMS were based on financial accounting standards which were adequate for most purposes. However, this study develops the fact that many of these financial accounting standards were created to provide information for equity market transactions. The complexities of accounting for consolidations will provide valuable information, but implementing these standards will require accounting sophistication that is not prevalent in agriculture.

By drawing accounting theory together with the targeted use of data, this study offers guidelines to improve the data quality for a growing complex US agriculture.

A major policy issue facing leaders in the developing world is whether international migration, through remittances, contributes to the development process in migrant-sending communities or impedes the efficient allocation of labor and human capital at the origin countries. This study examines the impact of remittance inflows on out-farm migration of farm labor toward the nonfarm sector. Specifically, this study shows how international migrant remittances may alter the predictions of out-farm migration models by Harris–Todaro.

The authors use unbalanced panel time-series data on 77 developing countries between 1991 and 2010 within a dynamic panel time-series framework to estimate the impact of remittances on the out-farm migration rate.

The authors find two competing effects of remittances on out-farm migration of labor in developing countries. First, remittances decelerate the out-farm migration rates by supplementing farm income and consumption expenditures. Second, remittances provide a source of investment in nonfarm activities that increase the rate of migration out of agriculture over time. Combining these effects, on average, our elasticity estimates indicate that a 10% increase in remittances reduces the migration out of agriculture, on average, by 0.5% in developing countries over time.

The authors findings align with the “developmentalist” or “optimistic” views of international migration. International migration, through remittances, help make the inevitable transition out of the farm sector smoother for developing countries.

To the authors’ knowledge, this is the first study to extend the empirical literature on macro-level determinants of out-farm migration within the Harris–Todaro framework to explicitly account for the impacts of remittances inflows into developing countries that the new economics of labor migration (NELM) theory hypothesizes.

The purpose of this paper is to examine investments in selected Feed the Future countries in Africa.

The authors examine three investments in Feed the Future countries (e.g. Rwanda and Uganda) in the context of non-traded goods, exports and imports. These investments include research and development in Ugandan cassava production, a value chain intervention in the coffee market channel in Rwanda and a program to increase the use of fertilizer for maize production in Rwanda. The authors also stress the importance of distributional impacts in terms of policymaking.

The results show that while there can be net gains from each investment discussed, the distributional effects of each are very different.

The findings will be useful for the development community and agribusiness policymaking.