Graduate Research Assistant, Farm Income Enhancement Program, Department of AEDE, The Ohio State University, August 2021-present

Graduate Research Assistant, GlobalWater Institute, College of Engineering, The Ohio State University, May-August 2021

Graduate Research Assistant, for Dr. Leah Bevis, Department of AEDE, The Ohio State University, May-August 2020

Chandio, R and Ani L. Katchova. “Sources of Bias in the USDA Baseline Projections.” Working Paper, Department of AEDE, The Ohio State University, 2022

Description: USDA’s annual Agricultural Baseline Projections contribute significantly to agricultural policy in the United States, and hence their accuracy is vital. The baseline projections present a neutral policy scenario assuming a specific macroeconomic situation and allow the analyses of alternative policies and their micro and macroeconomic impacts in the United States. We investigate the trends and heterogeneity in the incidence of bias in the USDA International Baseline Projection reports from 2002 to 2021. The evaluation of bias as it varies geographically, temporally, and by crop-variable allows us to make inferential judgments about the sources of this bias. First, we use the dynamic time warping algorithm to examine whether experts tend to group together the projections for certain crops across different countries, producing similar projection trends. We find that projection series for all countries in the sample are correlated with the United States in their trends. Second, we compute the bias in projections and decompose it by projection horizon. Third, we assess whether the bias is higher across crops or across countries with more substantial evidence for grouping behavior and find that for soybeans imports, soybeans ending stocks, and wheat area harvested, similarity in projection trends with the United States lowers the bias. At the same time, for most other crop-variables it increases it. This suggests that the projections for our sample countries are unnecessarily made to follow similar trends to the United States projections, which prove to be a bias-inducing choice in most cases. [link]

Chandio, R. ”Conservation and Conflicts in the Amazon.” Working Paper, Department of AEDE, The Ohio State University, 2022.

Description: This study evaluates how environmental policy restricting land use influences incentives for landowning farmers and landless peasants, and affects illegal occupations and land conflicts in the Brazilian Amazon. I use a ten-year panel data for conflicts, agriculture, and deforestation in the Legal Amazon region of Brazil and employ various matching methods to estimate the causal effect of an anti-deforestation policy on land conflicts and occupations. My estimates show the policy increases the number of illegal occupations in the Priority List municipalities by 25.9% while the number of land conflicts decreases by 21.5%. Analyzing the heterogeneity in the impact with respect to land values suggests that landowners and squatters both made strategic choices about whether to engage in conflict depending on the value of the land being contested. Landowners directed their efforts in capital and labor investments in their lands when the value of engaging in conflict to protect the occupied parcel of their lands was not more than the cost. But, for higher valued lands, landowners chose violent conflict to defend their plots. There are no spatial spillovers of the policy.

Chandio, R. and Leah E.M. Bevis. ”Winners and Losers in India’s Green Revolution.” Working Paper, Department of AEDE, The Ohio State University, 2022.

Description: The green revolution in India has been lauded for its positive impact on agricultural productivity and, in turn, the farmers’ lives. However, its effects on land redistribution and inequality, in the long run, are unclear. Large farmers may have benefited non-proportionately from the technologies that pervaded in the decades leading up to the turn of the 21st century. Richer farmers who own larger farms had early access to irrigation systems, allowing them to profit more. Simultaneously, the smaller farmers who are unable to set up new irrigation technologies and thus cannot compete with the large farmers may be forced to sell their farms, leading to systematic land redistribution. The poor farmers, in this process, may be worse off as a consequence of the green revolution in India. This raises the question whether the policy implementation considered farmer welfare at all. Identifying the winners and losers in the green revolution is important not only to understand the current inequality in India but also to design appropriate agrarian and welfare policies. Moreover, this research has policy relevance specifically for countries in Africa that are more recent to new agricultural technologies and may inadvertently experience worsened inequality and welfare loss by non-optimal policies.