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And because thou wast acceptable to God, it was necessary that temptation should prove thee. And now the Lord hath sent me to heal thee … — Tobit 12:13.

This week I wanted to discuss tobit estimators. In case you are not familiar with it, Wiki describes the tobit estimators (people say tobit “models,” but I don’t like calling estimators models, which confuses theory with empirics a bit too much for my taste) as

a statistical model proposed by James Tobin (1958) to describe the relationship between a non-negative dependent variable Y and an independent variable X. The term tobit was derived from Tobin’s name by truncating and adding -it by analogy with the probit model.

The model supposes that there is a latent (i.e. unobservable) variable Y*. This variable linearly depends on X via a parameter (vector) b which determines the relationship between the independent variable (or vector) X and the latent variable Y* (just as in a linear model). In addition, there is a normally distributed error term U to capture random influences on this relationship. The observable variable Y is defined to be equal to the latent variable whenever the latent variable is above zero and zero otherwise.

There are many types of tobits–Wiki lists five, which are such that

The Morrill Land-Grant Acts are the laws that led to the creation of a system of land-grant colleges in the United States. As per Wikipedia, land-grant colleges are universities whose “mission … is to focus on the teaching of practical agriculture, science, military science and engineering … as a response to the industrial revolution and changing social class.”

I have greatly benefited from the Morrill Act,* as have many of my friends and colleagues. In the state of New York, the designated land-grant institution is Cornell, where I went to grad school. In the state of Minnesota, that institution is the University of Minnesota, where I work. I spent most of–and the most fulfilling of–the last 15 years at land-grant institutions.

Is it time for a new Morrill Act? Austan Goolsbee, the University of Chicago economist who chaired President Obama’s Council of Economic Advisors, thinks so:

That is the title of my most recent article (co-authored with Chris Paul, Erika Weinthal, and Marc Jeuland), which is now published in Global Environmental Change. Here is the abstract:

Climate change is expected to have particularly severe effects on poor agrarian populations. Rural households in developing countries adapt to the risks and impacts of climate change both individually and collectively. Empirical research has shown that access to capital—financial, human, physical, and social—is critical for building resilience and fostering adaptation to environmental stresses. Little attention, however, has been paid to how social capital generally might facilitate adaptation through trust and cooperation, particularly among rural households and communities. This paper addresses the question of how social capital affects adaptation to climate change by rural households by focusing on the relationship of household and collective adaptation behaviors. A mixed-methods approach allows us to better account for the complexity of social institutions—at the household, community, and government levels—which drive climate adaptation outcomes. We use data from interviews, household surveys, and field experiments conducted in 20 communities with 400 households in the Rift Valley of Ethiopia. Our results suggest that qualitative measures of trust predict contributions to public goods, a result that is consistent with the theorized role of social capital in collective action. Yet qualitative trust is negatively related to private household-level adaptation behaviors, which raises the possibility that social capital may, paradoxically, be detrimental to private adaptation. Policymakers should account for the potential difference in public and private adaptation behaviors in relation to trust and social capital when designing interventions for climate adaptation.