Instead of laboratory: Analyzing data from natural experiments (Nobel Memorial Prize in Economic Sciences 2021)

2022 ◽  
pp. 5-22
Author(s):  
K. I. Sonin
Keyword(s):  
Empirical Analysis ◽  
Statistical Methods ◽  
Nobel Prize ◽  
Labor Economics ◽  
Natural Experiment ◽  
Heterogeneous Reactions ◽  
Causal Effects ◽  
Natural Experiments ◽  
Policy Changes ◽  
New Approach

The 2021 Nobel Prize in Economic Sciences was awarded to David Card, Joshua Angrist, and Guido Imbens for advancing methodology to establish casual relationships in economics. Their approach brought the notion of the natural experiment, situations in which heterogeneous reactions of different groups of people to chance shocks or policy changes allows to elicit causal effects, to the forefront of empirical analysis, and spearheaded a revolution in development of statistical methods needed to analyze the data. After the initial contributions in labor economics and economics of education, the new approach has become a new standard in economic sciences.

Natural Experiments Based on Geography

2015 ◽  
Vol 4 (1) ◽  
pp. 65-95 ◽  
Author(s):  
Luke Keele ◽  
Rocío Titiunik
Keyword(s):  
Natural Experiment ◽  
Original Study ◽  
Causal Effects ◽  
Natural Experiments ◽  
Ballot Initiatives ◽  
Causal Inferences ◽  
And Control ◽  
Administrative Boundary

Political scientists often attempt to exploit natural experiments to estimate causal effects. We explore how variation in geography can be exploited as a natural experiment and review several assumptions under which geographic natural experiments yield valid causal estimates. In particular, we focus on cases where a geographic or administrative boundary splits units into treated and control areas. The different identification assumptions we consider suggest testable implications, which we use to establish their plausibility. Our methods are illustrated with an original study of whether ballot initiatives increase turnout in Wisconsin and Ohio, which illustrates the strengths and weaknesses of causal inferences based on geographic natural experiments.

Recent and Planned Developments of the Program OxCal

Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 720-730 ◽  
Author(s):  
Christopher Bronk Ramsey ◽  
Sharen Lee
Keyword(s):  
Statistical Analysis ◽  
Statistical Methods ◽  
Software Package ◽  
Model Averaging ◽  
Data Sets ◽  
Radiocarbon Dates ◽  
New Approach ◽  
New Models ◽  
Multiphase Models ◽  
Deposition Models

OxCal is a widely used software package for the calibration of radiocarbon dates and the statistical analysis of 14C and other chronological information. The program aims to make statistical methods easily available to researchers and students working in a range of different disciplines. This paper will look at the recent and planned developments of the package. The recent additions to the statistical methods are primarily aimed at providing more robust models, in particular through model averaging for deposition models and through different multiphase models. The paper will look at how these new models have been implemented and explore the implications for researchers who might benefit from their use. In addition, a new approach to the evaluation of marine reservoir offsets will be presented. As the quantity and complexity of chronological data increase, it is also important to have efficient methods for the visualization of such extensive data sets and methods for the presentation of spatial and geographical data embedded within planned future versions of OxCal will also be discussed.

Natural “Natural Experiments” in Economics

2000 ◽  
Vol 38 (4) ◽  
pp. 827-874 ◽  
Author(s):  
Mark R Rosenzweig ◽  
Kenneth I Wolpin
Keyword(s):  
Natural Experiment ◽  
Recent Literature ◽  
Economic Models ◽  
Empirical Knowledge ◽  
Natural Experiments ◽  
Simple Economic

The recent literature exploiting natural events as “natural experiment” instruments is reviewed to assess to what extent it has advanced empirical knowledge. A weakness of the studies that adopt this approach is that the necessary set of behavioral, market, and technological assumptions made by the authors in justifying their interpretations of the estimates is often absent. The methodology and findings from twenty studies are summarized and simple economic models are used to elucidate the implicit assumptions made by the authors and to demonstrate the sensitivity of the interpretations of the findings to the relaxation of some of these assumptions.

scholarly journals Built environment changes and active transport to school among adolescents: BEATS Natural Experiment Study protocol

BMJ Open ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. e034899 ◽  
Author(s):  
Sandra Mandic ◽  
Debbie Hopkins ◽  
Enrique García Bengoechea ◽  
Antoni Moore ◽  
Susan Sandretto ◽  
...  
Keyword(s):  
New Zealand ◽  
Built Environment ◽  
Active Transport ◽  
Natural Experiment ◽  
Information Science ◽  
Controlled Trial ◽  
Natural Experiments ◽  
Scientific Publications ◽  
Social Environmental ◽  
Randomised Controlled

IntroductionNatural experiments are considered a priority for examining causal associations between the built environment (BE) and physical activity (PA) because the randomised controlled trial design is rarely feasible. Few natural experiments have examined the effects of walking and cycling infrastructure on PA and active transport in adults, and none have examined the effects of such changes on PA and active transport to school among adolescents. We conducted the Built Environment and Active Transport to School (BEATS) Study in Dunedin city, New Zealand, in 2014–2017. Since 2014, on-road and off-road cycling infrastructure construction has occurred in some Dunedin neighbourhoods, including the neighbourhoods of 6 out of 12 secondary schools. Pedestrian-related infrastructure changes began in 2018. As an extension of the BEATS Study, the BEATS Natural Experiment (BEATS-NE) (2019–2022) will examine the effects of BE changes on adolescents’ active transport to school in Dunedin, New Zealand.Methods and analysisThe BEATS-NE Study will employ contemporary ecological models for active transport that account for individual, social, environmental and policy factors. The published BEATS Study methodology (surveys, accelerometers, mapping, Geographic Information Science analysis and focus groups) and novel methods (environmental scan of school neighbourhoods and participatory mapping) will be used. A core component continues to be the community-based participatory approach with the sustained involvement of key stakeholders to generate locally relevant data, and facilitate knowledge translation into evidence-based policy and planning.Ethics and disseminationThe BEATS-NE Study has been approved by the University of Otago Ethics Committee (reference: 17/188). The results will be disseminated through scientific publications and symposia, and reports and presentations to stakeholders.Trial registration numberACTRN12619001335189.

Observing the Counterfactual? The Search for Political Experiments in Nature

2009 ◽  
Vol 17 (4) ◽  
pp. 341-357 ◽  
Author(s):  
Gregory Robinson ◽  
John E. McNulty ◽  
Jonathan S. Krasno
Keyword(s):  
Political Science ◽  
Research Design ◽  
Natural Experiment ◽  
Science Literature ◽  
Natural Experiments ◽  
Special Issue ◽  
Methodological Issues ◽  
Introductory Essay ◽  
Conference Presentations

A search of recent political science literature and conference presentations shows substantial fascination with the concept of the natural experiment. However, there seems to be a wide array of definitions and applications employed in research that purports to analyze natural experiments. In this introductory essay to the special issue, we attempt to define natural experiments and discuss related issues of research design. In addition, we briefly explore the basic methodological issues around the appropriate analysis of natural experiments and give an overview of different techniques. The overarching theme of this essay and of this issue is to encourage applied researchers to look for natural experiments in their own work and to think more systematically about research design.

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