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Open Access Publications from the University of California

The University of California, Berkeley offers the premier graduate program in Agricultural and Resource Economics.* Graduate studies in this department emphasize a firm foundation in economic analysis and quantitative methods and their application to agricultural economics, environmental and resource economics, international agricultural trade and development, intellectual property rights and biotechnology, agribusiness/marketing/finance, and applied econometrics. The faculty have a distinguished research and public service record, having received numerous research awards, and played a major advisory role in shaping agricultural, resource and environmental policies. Fourteen faculty members of ARE have been elected Fellows of the American Agricultural Economics Association (AAEA) and three are currently Fellows of the Econometric Society.

The papers below are part of the CUDARE (California, University. Department of Agricultural and Resource Economics) working paper series, which began in 1976. The series has over 1000 papers, many of which have been digitized by the Giannini Foundation of Agricultural Economics Library Staff.

*Perry, Gregory M. 1994. "Ranking M.S. and Ph.D. Graduate Programs in Agricultural Economics." Review of Agricultural Economics 16:333-40.

Photo of Giannini Hall by Grace Dote

Papers are uploaded to this site by the Giannini Foundation Library staff.

Cover page of SMS Surveys of Selected Expenditures

SMS Surveys of Selected Expenditures


High-frequency measures of economic well-being can allow policymakers and researchers to understand and quickly respond to dynamic problems, but collecting such data is expensive. Can short message service (SMS) surveys enable researchers and policymakers to measure household welfare and firm performance at a high frequency in low-income countries? We detail the implementation of two SMS surveys and evaluate their efficacy for gathering high-frequency data. One measures consumption expenditures in Rwanda and the other measures microenterprise revenues in Uganda. We successfully calculate a measure of household welfare for households that respond to the SMS survey in Rwanda and track changes in revenues over time for microenterprises in Uganda. Our SMS surveys are substantially less costly than equivalent in-person surveys; however, nonresponse is a significant problem. We propose combining SMS surveys with in-person data collection to compute weights that correct for nonresponse bias, then evaluate the performance of our method using the revenues data from Uganda.

Cover page of Reduce, Reuse, Redeem: Deposit-Refund Recycling Programs in the Presence of Alternatives

Reduce, Reuse, Redeem: Deposit-Refund Recycling Programs in the Presence of Alternatives


We estimate consumer preferences and willingness to pay for current beverage container recycling methods, including curbside pick-up services, drop-off at government-subsidized recycling centers, and drop-off at non-subsidized centers. Using a representative online and telephone survey of California households, we estimate a discrete choice model that identifies the key attributes explaining consumers’ beverage container disposal decisions: the refund amount (paid to consumers only if they recycle at drop-off centers), the volume of recyclable material generated by the household, and the effort associated with bringing recyclable materials to recycling centers. Additionally, we use counterfactual policy analy- sis to show that increasing the refund amount increases overall recycling rates, with the largest changes in consumer surplus accruing to inframarginal consumers, who are on the boundary between taking containers to recycling centers and recycling using curbside pick-up, namely white and higher income consumers. Conversely, we show that eliminating government-subsidized drop-off centers does not significantly alter consumer surplus for any major demographic group, and has little impact on recycling rates.

Cover page of Inferring informal risk-sharing regimes: Evidence from rural Tanzania

Inferring informal risk-sharing regimes: Evidence from rural Tanzania


This paper studies informal risk-sharing regimes in a unified framework by examining intertemporal consumption behavior of rural households in Tanzania. We exploit  a theoretically-consistent link between interest rates and cross-sectional consumption moments to test alternative risk-sharing models without requiring data on interest rates or assuming a restriction to eliminate the need for such data, which are often unavailable in developing economies. We specify tests that allow us to distinguish among models even with temporal dependence in income shocks. Our analysis shows that the consumption pattern in rural Tanzania is consistent with the self-insurance regime, and that risk aversion varies substantially across districts. Imposing a strict condition on interest rates, as often done in prior literature, misses their intertemporal heterogeneity and biases the estimation of risk aversion.

Cover page of The Environmental Bias of Trade Policy

The Environmental Bias of Trade Policy


This paper documents a new fact, then analyzes its causes and consequences: in most countries, import tariffs and non-tariff barriers are substantially lower on dirty than on clean industries, where an industry’s “dirtiness” is defined as its carbon dioxide (CO2) emissions per dollar of output. This difference in trade policy creates a global implicit subsidy to CO2 emissions in internationally traded goods and so contributes to climate change. This global implicit subsidy to CO2 emissions totals several hundred billion dollars annually. The greater protection of downstream industries, which are relatively clean, substantially accounts for this pattern. The downstream pattern can be explained by theories where industries lobby for low tariffs on their inputs but final consumers are poorly organized. A quantitative general equilibrium model suggests that if countries applied similar trade policies to clean and dirty goods, global CO2 emissions would decrease and global real income would change little

Cover page of Are We #StayingHome to Flatten the Curve?

Are We #StayingHome to Flatten the Curve?


The recent spread of COVID-19 across the U.S. led to concerted efforts by states to ``flatten the curve" through the adoption of stay-at-home mandates that encourage individuals to reduce travel and maintain social distance. Combining data on changes in travel activity with COVID-19 health outcomes and state policy adoption timing, we characterize nationwide changes in mobility patterns and isolate the portion attributable to statewide mandates. We find evidence of dramatic nationwide declines in mobility prior to adoption of any statewide mandates. Once states adopt a mandate, we estimate further mandate-induced declines between 2.1 and 7.0 percentage points across methods that account for states' differences in travel behavior prior to policy adoption. In addition, we investigate the effects of stay-at-home mandates on changes in COVID-19 health outcomes while controlling for pre-trends and observed pre-treatment mobility patterns. We estimate mandate-induced declines between 0.13 and 0.17 in deaths (5.6 to 6.0 in hospitalizations) per 100 thousand across methods. Across 43 adopting states, this represents 23,366-30,144 fewer deaths (and roughly one million averted hospitalizations) for the months of March and April - which indicates that death rates could have been 42-54% higher had states not adopted statewide policies. We further find evidence that changes in mobility patterns prior to adoption of statewide policies also played a role in reducing COVID-19 mortality and morbidity. Adding in averted deaths due to pre-mandate social distancing behavior, we estimate a total of 48-71,000 averted deaths from COVID-19 for the two-month period. Given that the actual COVID-19 death toll for March and April was 55,922, our estimates suggest that deaths would have been 1.86-2.27 times what they were absent any stay-at-home mandates during this period. These estimates represent a lower bound on the health impacts of stay-at-home policies, as they do not account for spillovers or undercounting of COVID-19 mortality. Our findings indicate that early behavior changes and later statewide policies reduced death rates and helped attenuate the negative consequences of COVID-19. Further, our findings of substantial reductions in mobility prior to state-level policies convey important policy implications for re-opening.

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