Gulcan Onel

Off-farm Labor Allocation, Income, and Food Consumption among Rural Farm Households in Transitional Albania

Abstract Purpose We analyze the food security implications of off-farm labor reallocation decisions of rural farm households in transitional Albania. We accomplish this by examining local and nonlocal off-farm incomes for at-home food consumption expenditures. Methodology/approach An instrumental variable approach is employed to correct for endogeneity and censorship biases of off-farm income variables in a two-stage estimation of the food consumption expenditures. Findings We find that local off-farm income exerts a positive and significant effect on per capita food consumption expenditures of farm households, while private remittances from nonlocal off-farm income has the opposite effect on food consumption expenditures. In terms of regional heterogeneity, we discover that the mountain region spends significantly less on annual per capita food consumption compared to the central region. This confirms anecdotal evidence that food and nutrition insecurity in rural Albania is predominant in the mountain region. Social implications Our findings suggest the need for policy makers to promote a development agenda that enables farm households to exploit the synergies among the various income-generating activities in the rural economy. This spectrum of income-generating activities forms complex livelihood strategies adopted by rural farm households to improve and maintain their food security. Originality/value We distinguish between local and nonlocal sources of off-farm income. Knowing which off-farm income source(s) has the largest impact on household welfare through improved food security status should be of interest to policy makers.

Do producers respond to every input price change? A note on nonlinearities in factor demand systems

Factor demand relationships, as they are represented by parameters of the cost function, are generally assumed to be linear (in the parameters) in the existing empirical literature. In this note, we argue that this might not always be true, because firms may incur adjustment costs that are inherent in the act of adjusting the mix of inputs applied in the underlying production technologies. We estimate a two-regime threshold system of factor demand equations for several manufacturing industries in the United States. Our results suggest significant nonlinear effects in the factor demand relationships in most nondurable goods sectors. Failure to account for this threshold sensitivity to input price change may cause the estimates of price elasticities to be biased.Factor demand relationships, as they are represented by parameters of the cost function, are generally assumed to be linear (in the parameters) in the existing empirical literature. In this note, we argue that this might not always be true, because firms may incur adjustment costs that are inherent in the act of adjusting the mix of inputs applied in the underlying production technologies. We estimate a two-regime threshold system of factor demand equations for several manufacturing industries in the United States. Our results suggest significant nonlinear effects in the factor demand relationships in most nondurable goods sectors. Failure to account for this threshold sensitivity to input price change may cause the estimates of price elasticities to be biased.

Adjustment costs and threshold effects in factor demand relationships

ABSTRACT It has been recently argued that producers may not respond to every input price change in the way that a linear factor demand model would predict. This lumpy response is due to adjustment costs that are inherent in the act of adjusting the mix of inputs applied in the underlying production technologies. This study aims to provide a solid conceptual framework for these nonlinearities in factor demand relationships. Industry-specific implications of convex and non-convex adjustment costs for the linearity of the factor demand relationships as well as price and substitution elasticities are explored. A two-regime threshold system of factor demand equations is estimated for several manufacturing industries in the United States. Empirical results suggest significant threshold effects in the factor demand relationships in most nondurable goods sectors. The size and the nature of thresholds depend upon industry characteristics, including input composition and (non)convexity of underlying adjustment costs. Complete matrices of price and substitution elasticities for each industry are derived using estimates of threshold factor demand systems. Discussion of two contrasting cases in greater detail sheds light on how the effect of price shocks on factor demand relationships varies across industries with different adjustment cost structures.

Asset concentration in the US agricultural balance sheet: a relative information approach

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.