David Zilberman

Bio: David Zilberman is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Reporting bias & Consumption (economics). The author has an hindex of 10, co-authored 36 publications receiving 665 citations.

Climate Smart Agriculture: Building Resilience to Climate Change

Abstract: Chapter 1: Introduction.- Chapter 2: A Short History of the Evolution of the Climate Smart Agriculture Approach and its Links to Climate Change and Sustainable Agriculture Debates.- Chapter 3:Economics of Climate-Smart Agriculture.- Chapter 4: Innovation in Response to Climate Change.- Chapter 5: Use of Satellite Information on Wetness and Temperature for Decision of Crop Yield Prediction, River Discharge and Planning.- Chapter 6: Early Warning Techniques for Local Climate Resilience: Smallholder Rice in Lao PDE.- Chapter 7 : Farmers' Perceptions of and Adaptations to Climate Change in Southeast Asia: The Case Study from Thailand and Vietnam.- Chapter 8: U.S. Maize Yield Growth and Countervailing Climate Change Impacts.- Chapter 9: Understanding Tradeoffs in the Context of Farm-Scale Impacts: An Application of Decision-Support Tools for Assessing Climate Smart Argiculture.- Chapter 10: Can Insurance Help Manage Climate Risk and Food Insecurity?: Evidence from the Pastoral Regions of East Africa.- Chapter 11: Can Cash Transfer Programs Promote Household Resilience?: Cross-Country Evidence from Sub-Saharan Africa.- Chapter 12: Input Subsidy Programs and Climate Smart Agriculture.- Chapter 13: Robust Decision Making for a Climate-Resilient Development of the Agricultural Sector in Nigeria.- Chapter 14: Using AgMIP Regional Integrated Assessment Methods to Evaluate Vulnerability, Resilience and Adaptive Capacity for Climate Smart Agricultural Systems.- Chapter 15: Climate Smart Food Supply Chains in Developing Countries in an Era of Rapid Dual Change in Agrifood Systems and the Climate.- Chapter 16: The Adoption of Climate Smart Agriculture: The Role of Information and Insurance under Climate Change.- Chapter 17: A Qualitative Evaluation of CSA Options in Mixed Crop-Livestock Systems in Developing Countries.- Chapter 18: Identifying Strategies to Enhance the Resilience of Smallholder Farming Systems: Evidence of Zambia.- Chapter 19: Climate Risk Management Through Sustainable Land and Water Management in Sub-Saharan Africa.- Chapter 20: Improving the Resilience of Central Asian Agriculture to Weather Viability and Climate Change.- Chapter 21: Managing Environmental Risk in the Presence of Climate Change: The Role of Adaption in the Mile Basin of Ethiopia.- Chapter 22: Diversification as Part of a CSA Strategy: The Cases of Zambia and Malawi.- Chapter 23: Economic Analysis of Improved Smallholder Paddy and Maize Production in Northern Vietnam and Implications for Climate-Smart Agriculture.- Chapter 24: Synthesis: Devising Effective Strategies and Policies for CSA.- Chapter 25: Conclusions and Policy Implications.

Fat Taxes And Thin Subsidies: Prices, Diet, And Health Outcomes

Abstract: "Fat taxes" have been proposed as a way of addressing food-related health concerns. In this paper, we investigate the possible effects of "thin subsidies," consumption subsidies for healthier foods. Empirical simulations, based on data from the Continuing Study of Food Intake by Individuals, are used to calculate the potential health benefits of subsidies on certain classes of fruits and vegetables. Estimates of the cost per statistical life saved through such subsidies compare favorably with existing U.S. government programs.

Fat taxes and thin subsidies: Prices, diet, and health outcomes

Abstract: “Fat taxes” have been proposed as a way of addressing food-related health concerns. In this paper, we investigate the possible effects of “thin subsidies”, consumption subsidies for healthier foods. Empirical simulations, based on data from the Continuing Study of Food Intake by Individuals, are used to calculate the potential health benefits of subsidies on certain classes of fruits and vegetables in the United States. Estimates of the cost per statistical life saved through such subsidies compare favorably with existing U.S. government programs.

Selective Reporting and the Social Cost of Carbon

Abstract: We examine potential selective reporting in the literature on the social cost of carbon (SCC) by conducting a meta-analysis of 809 estimates of the SCC reported in 101 studies. Our results indicate that estimates for which the 95% confidence interval includes zero are less likely to be reported than estimates excluding negative values of the SCC, which might create an upward bias in the literature. The evidence for selective reporting is stronger for studies published in peer-reviewed journals than for unpublished papers. We show that the findings are not driven by the asymmetry of the confidence intervals surrounding the SCC and are robust to controlling for various characteristics of study design and to alternative definitions of confidence intervals. Our estimates of the mean reported SCC corrected for the selective reporting bias are imprecise and range between USD 0 and 130 per ton of carbon at 2010 prices for emission year 2015.

Likelihood Based Inference In Cointegrated Vector Autoregressive Models

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Climate Change Policy: What Do the Models Tell Us?

Abstract: †Very little. A plethora of integrated assessment models (IAMs) have been constructed and used to estimate the social cost of carbon (SCC) and evaluate alternative abatement policies. These models have crucial flaws that make them close to useless as tools for policy analysis: certain inputs (e.g., the discount rate) are arbitrary, but have huge effects on the SCC estimates the models produce; the models’ descriptions of the impact of climate change are completely ad hoc, with no theoretical or empirical foundation; and the models can tell us nothing about the most important driver of the SCC, the possibility of a catastrophic climate outcome. IAM-based analyses of climate policy create a perception of knowledge and precision, but that perception is illusory and misleading. ( JEL C51, Q54, Q58)

Meta-Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection

Abstract: This study investigates the small-sample performance of meta-regression methods for detecting and estimating genuine empirical effects in research literatures tainted by publication selection. Publication selection exists when editors, reviewers or researchers have a preference for statistically significant results. Meta-regression methods are found to be robust against publication selection. Even if a literature is dominated by large and unknown misspecification biases, precision-effect testing and joint precision-effect/meta-significance testing can provide viable strategies for detecting genuine empirical effects. Publication biases are greatly reduced by combining two biased estimates, the estimated meta-regression coefficient on precision (1/Se) and the unadjusted average effect.