Suchergebnisse

AbstractMany researchers use an ordinal scale to quantitatively measure and analyze concepts. Theoretically valid empirical estimates are robust in sign to any monotonic increasing transformation of the ordinal scale. This presents challenges for the point-identification of important parameters of interest. I develop a partial identification method for testing the robustness of empirical estimates to a range of plausible monotonic increasing transformations of the ordinal scale. This method allows for the calculation of plausible bounds around effect estimates. I illustrate this method by revisiting analysis by Nunn and Wantchekon (2011, American Economic Review, 101, 3221–3252) on the slave trade and trust in sub-Saharan Africa. Supplemental illustrations examine results from (i) Aghion et al. (2016, American Economic Review, 106, 3869–3897) on creative destruction and subjective well-being and (ii) Bond and Lang (2013, The Review of Economics and Statistics, 95, 1468–1479) on the fragility of the black–white test score gap.

AbstractIn the early days of the COVID‐19 pandemic, we launched the Online Agricultural and Resource Economics Seminar (OARES) in an ostensible effort to maintain a semblance of normalcy in agricultural and applied economics. Our goal with the OARES was to break down the privilege barrier in two ways: by (i) featuring research mainly by junior, female, or minority scholars, and (ii) bringing frontier research to those who may not have had access to a regular seminar series prior to the pandemic. We thus discuss the contribution of the OARES to diversity, equity, inclusion, and belonging in agricultural and applied economics.

Governments, multinational companies, and researchers today collect unprecedented amounts of data on human feelings. These data provide information on citizens' happiness, levels of customer satisfaction, employees' satisfaction, mental stress, societal trust, and other important variables. Yet a key scientific difficulty tends to be downplayed, or even ignored, by many users of such information. Human feelings are not measured in objective cardinal units. This paper aims to address some of the ensuing empirical challenges. It suggests an analytical way to approach the scientific complications of ordinal data. The paper describes a dichotomous-around-the-median (DAM) test, which, crucially, uses information only on direction within an ordering and deliberately discards the potentially unreliable statistical information in ordered data. Applying the proposed DAM approach, the paper demonstrates that it is possible to check and replicate some of the key conclusions of previous research—including earlier work on the effects upon human well-being of higher income.

This paper documents some of the first estimates of the effect of the coronavirus pandemic on food security in a low- and middle-income country context. It combines nationally representative pre- pandemic household survey data with follow-up phone survey data from Mali and exploits sub- national variation in the intensity of pandemic-related disruptions between urban and rural areas. These disruptions stem from both government policies aiming to slow the spread of the virus and also individual behavior motivated by fear of contracting the virus. The paper finds evidence of increasing food insecurity in Mali associated with the pandemic. Difference-in-difference estimates show that moderate food insecurity increased by about 8 percentage points -- a 33 percent increase -- in urban areas compared with rural areas in Mali. The estimates are substantially larger than existing predictions of the average effect of the pandemic on food security globally and therefore highlights the critical importance of understanding effect heterogeneity.