scholarly journals Human Suffering and Natural Experiments: How Empirical Economics can unmask the devastation of Covid-19

2021 ◽  
Vol 47 (4) ◽  
pp. 461-463
Author(s):  
Alexandre Olbrecht
2010 ◽  
Vol 24 (2) ◽  
pp. 31-46 ◽  
Author(s):  
Edward E Leamer

My first reaction to “The Credibility Revolution in Empirical Economics,” authored by Joshua D. Angrist and Jörn-Steffen Pischke, was: Wow! This paper makes a stunningly good case for relying on purposefully randomized or accidentally randomized experiments to relieve the doubts that afflict inferences from nonexperimental data. On further reflection, I realized that I may have been overcome with irrational exuberance. Moreover, with this great honor bestowed on my “con” article, I couldn't easily throw this child of mine overboard. As Angrist and Pischke persuasively argue, either purposefully randomized experiments or accidentally randomized “natural” experiments can be extremely helpful, but Angrist and Pischke seem to me to overstate the potential benefits of the approach. I begin with some thoughts about the inevitable limits of randomization, and the need for sensitivity analysis in this area, as in all areas of applied empirical work. I argue that the recent financial catastrophe is a powerful illustration of the fact that extrapolating from natural experiments will inevitably be hazardous. I discuss how the difficulties of applied econometric work cannot be evaded with econometric innovations, offering as examples some under-recognized difficulties with instrumental variables and robust standard errors. I conclude with comments about the shortcomings of an experimentalist paradigm as applied to macroeconomics, and some warnings about the willingness of applied economists to apply push-button methodologies without sufficient hard thought regarding their applicability and shortcomings.


PsycCRITIQUES ◽  
2008 ◽  
Vol 53 (2) ◽  
Author(s):  
James Campbell Quick
Keyword(s):  

2011 ◽  
Author(s):  
Erika L. Rosenberg ◽  
Anthony P. Zanesco ◽  
Brandon G. King ◽  
Stephen R. Aichele ◽  
Tonya L. Jacobs ◽  
...  

MIS Quarterly ◽  
2017 ◽  
Vol 41 (4) ◽  
pp. 1035-1058 ◽  
Author(s):  
Ni Huang ◽  
◽  
Yili Hong ◽  
Gordon Burtch ◽  
◽  
...  

2018 ◽  
Author(s):  
Jaime Derringer

Although correlations between personality and health are consistently observed, often the causal pathway, or even the direction of effect, is unknown. Genes provide an additional node of information which may be included to help clarify the relationship between personality and health. Genetically informative studies, whether focused on family-identified relationships or specific genotypes, provide clear benefits to disentangling causal processes. Genetic measures approach near universal reliability and validity: processes of inheritance are consistent across cultures, geography, and time, such that similar models and instruments may be applied to incredibly diverse populations. Although frequency and intercorrelations differ by ancestry background (Novembre et al., 2008) and cultural context (Tucker-Drob & Bates, 2016) may exert powerful moderating effects, fundamental form and function is consistent across all members of our species, and even many other species. Genetic sequence information is also of course highly temporally stable, and possesses temporal precedence. That is, the literal genetic sequence is lifetime-stable and comes before all other experiences. Human behavior genetic research, like most personality research, faces limitations in terms of causal inferences that may be made in the absence of experimental manipulation. But behavior genetics takes advantage of natural experiments: populations that differ in terms of genetic similarity (either inferred – such as twins – or measured – such as genotyping methods) to begin to unravel the complex influences on individual differences in personality and health outcomes.


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