2017
DOI: 10.1016/j.jdeveco.2017.05.004
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Market failures and misallocation

Abstract: I develop a method to measure and separate the production misallocation caused by failures in factor markets versus financial markets. When

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Cited by 27 publications
(13 citation statements)
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“…For instance, Dillon and Barrett (2017), Aggarwal et al (2018) (2019) documents distortions in input markets (measured using shadow prices) correlated with farm size in Malawi, Tanzania, and Uganda.. Similarly, several studies suggest that in some contexts (like Thailand, China, Malawi, Ethiopia, and Bangladesh) the agricultural production function of subsistence farmers may exhibit decreasing returns to scale (Shenoy, 2017;Chari et al, 2020;Restuccia and Santaeulàlia-Llopis, 2017;Gautam and Ahmed, 2019;Chen et al, 2021). We document similar findings of DRS in our empirical analysis using data from Uganda, Tanzania, Bangladesh and Peru.…”
Section: The Production Function Approach and Plot-level Regressionsmentioning
confidence: 99%
“…For instance, Dillon and Barrett (2017), Aggarwal et al (2018) (2019) documents distortions in input markets (measured using shadow prices) correlated with farm size in Malawi, Tanzania, and Uganda.. Similarly, several studies suggest that in some contexts (like Thailand, China, Malawi, Ethiopia, and Bangladesh) the agricultural production function of subsistence farmers may exhibit decreasing returns to scale (Shenoy, 2017;Chari et al, 2020;Restuccia and Santaeulàlia-Llopis, 2017;Gautam and Ahmed, 2019;Chen et al, 2021). We document similar findings of DRS in our empirical analysis using data from Uganda, Tanzania, Bangladesh and Peru.…”
Section: The Production Function Approach and Plot-level Regressionsmentioning
confidence: 99%
“…To achieve this goal, we first calculate the aggregate TFP and then decompose it into mean TFP and resource reallocation. Previous studies have either used farm‐level data (e.g., Sheng et al., 2017; Shenoy, 2017) or employed provincial‐level data (e.g., Diao et al., 2018; Sheng et al., 2020) in their estimations, limiting their generalization. In comparison, measuring the overall resource reallocation effects from the county level rather than farm level or provincial level would provide more valuable insights regarding the association between resource reallocation and agricultural productivity across regions.…”
Section: Introductionmentioning
confidence: 99%
“…For example, by analyzing the farm-level data in Australia broadacre agriculture, Sheng et al (2017) found that cross-farm resource reallocation contributed to 50% of industry-level productivity growth during 1978-2010. A study on rice-farming households in Thailand by Shenoy (2017) reveals that the optimal resource reallocation would increase rice output by about 19%. In their study of dairy farms in southeast Germany, Frick and Sauer (2018) showed that efficient resource reallocation would contribute to productivity growth by 1.5%.…”
Section: Introductionmentioning
confidence: 99%
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“…8 Our context allows us to innovate by demonstrating that separation failures induce differential adoption of irrigation on technologically identical plots. In doing so, we also contribute to a literature leveraging production function estimates to document misallocation of labor and inputs by inferring their marginal products from their allocations across plots or households (Jacoby, 1993;Skoufias, 1994;Udry, 1996;Shenoy, 2017;Restuccia & Santaeulalia-Llopis, 2017). 9 Our test for inefficient technology adoption caused by land and labor market failures therefore complements this literature, by both imposing less structure and leveraging our plot-level discontinuity in access to irrigation as an exogenous labor-and input-complementing productivity shock.…”
Section: Introductionmentioning
confidence: 99%