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This paper specifies the panel data experimental design condition under which ordinary least squares, fixed effects, and random effects estimators yield identical estimates of treatment effects. This condition is relevant to the large body of laboratory experimental research that generates panel data. Although the point estimates and the true standard errors of the estimated average treatment effects are identical across the three estimators, the estimated standard errors differ. A standard F test as well as asymptotic reasoning guide the choice of which estimated standard errors are the appropriate ones to use for statistical inference.
Chapter 3 establishes that the Dutch had economic incentives to continue holding slaves. Slavery in Dutch New York was not just a cultural choice, but was reinforced by economic considerations. From archival sources and published secondary sources, I have compiled a unique dataset of prices for over 3,350 slaves bought, sold, assessed for value, or advertised for sale in New York and New Jersey. This data has been coded by sex, age, county, price, and type of record, among other categories. It is as far as I know the only slave price database for slaves in the Northern states yet assembled. Regression analysis allows us to compute the average price of Northern slaves over time, the relative price difference between male and female slaves, the price trend relative to known prices in the American South, and other variables such as the price differential between New York City slaves and slaves in other counties in the state. Slave prices in New York and New Jersey appear relatively stable over time, but declined in the nineteenth century. The analysis shows that slaveholders in Dutch New York were motivated by profit, and they sought strength and youth in purchasing slaves.
Economists have long studied policy choice by social planners aiming to maximize population welfare. Whether performing theoretical studies or applied analyses, researchers have generally assumed that the planner knows enough about the choice environment to be able to determine an optimal action. However, the consequences of decisions are often highly uncertain. Discourse on Social Planning under Uncertainty addresses the failure of research to come to grips with this uncertainty. Combining research across three fields – welfare economics, decision theory, and econometrics – this impressive study offers a comprehensive treatment that fleshes out a 'worldview' and juxtaposes it with other viewpoints. Building on multiple case studies, ranging from medical treatment to climate policy, the book explains analytical methods and how to apply them, providing a foundation on which future interdisciplinary work can build.
In recent times, the economic and social relevance of constitutions and potential determinants of their validity have been increasingly debated. However, we still know little about the relationships between the text of a constitution and constitutional compliance. Does the wording of a constitution matter in this context? In this paper, drawing on a sample of democratic countries, we apply econometric and machine learning tools to provide some insights on these issues. The results suggest that shorter texts and placing more emphasis on punishments for transgressions seem to be positively correlated with the compliance level. Regarding the precision of constitutional text, in turn, we find mixed evidence. Econometric modelling suggests no statistically significant relationship with constitutional compliance, and machine learning models instead indicate this feature as a potentially important determinant of constitutional compliance.
This chapter provides a motivation for this book, outlining the interests of economists in artificial intelligence, describing who this book is aimed at, and laying out the structure of the book.
Livestock abortion is a source of economic loss for farmers, but its economic impact has not been estimated in many Low and Middle-Income Countries. This article presents an estimation methodology and estimates for the gross and net cost of an abortion based on a sample of livestock-owning households in three regions of northern Tanzania and market data. We then generate aggregate estimates of abortion losses across Tanzania. We estimate annual gross and net annual losses of about $263 Million (about TZS 600 billion) and $131 million (about TZS 300 billion), respectively.
We discuss how three social science disciplines, economics, sociology, and political science approach history and we contrast them to history as practiced by historians. We find that the drive to identify broadly generalizable causal effects, driven by the desire to predict and shape the future (the “Delphi syndrome”), frequently prompts social scientists to use history in a way that neglects the historians’ valuable insights. At the same time, the recent methodological developments in econometric techniques that have spread through the three disciplines place enormous, often unrealistic, historical demands on social scientists. We illustrate these issues by discussing several examples and we conclude by arguing that a way ahead consists in approaching the relation between idiographic and nomothetic research principles as one that approximates a continuum rather than a dichotomy.
Quantitative social scientists use survival analysis to understand the forces that determine the duration of events. This Element provides a guideline to new techniques and models in survival analysis, particularly in three areas: non-proportional covariate effects, competing risks, and multi-state models. It also revisits models for repeated events. The Element promotes multi-state models as a unified framework for survival analysis and highlights the role of general transition probabilities as key quantities of interest that complement traditional hazard analysis. These quantities focus on the long term probabilities that units will occupy particular states conditional on their current state, and they are central in the design and implementation of policy interventions.
Residential energy efficiency programs play an important role in combating climate change. More precise quantification of the magnitude and timing of energy savings would bring large system benefits, allowing closer integration of energy efficiency into resource adequacy planning and balancing variable renewable electricity. However, it is often difficult to quantify the efficacy of an energy efficiency intervention, because doing so requires consideration of a hypothetical counterfactual case in which there was no intervention, and randomized control trials are often implausible. Although quasi-experimental econometric evaluation sometimes works well, we find that for a set of energy efficiency rebate programs in Northern California, a naïve interpretation of econometric measurement finds that rebate participation is associated with an average increase in electricity consumption of 7.2% [4.5%, 10.1%], varying in magnitude and sign depending on the type of appliance or service covered by the rebate. A subsequent household survey on appliance purchasing behavior and analysis of utility customer outreach data suggest that this regression approach is likely measuring the gross impact of buying a new appliance but fails to adequately capture a counterfactual comparison. Indeed, it is unclear whether it is even possible to construct a suitable counterfactual for econometric analyses of these rebate programs using data generally available to electric utilities. We view these results as an illustration of a limitation of econometric methods of program evaluation and the importance of weighing engineering modeling and other imperfect methods against one another when attempting to provide useful evaluations of real-world policy interventions.
A key response to legitimacy concerns over investment arbitration has been to point to the contribution of investment treaties to significant increases in in-bound foreign investment. The authors return to this vexed question of whether treaties offer material benefits and the large literature on the topic. Through a mixed methods approach and heightened awareness of the synergies and tensions within and between methodological approaches, they: (1) analyse econometrically the impact of ISDS provisions on inbound FDI; (2) present new qualitative research on investor and host state practices and attitudes; and (3) argue that social psychological research on cultural risk cognition is useful for both framing and presenting research questions and findings. They conclude that whatever the results that emerge from empirical research findings, the form of presentation will determine whether they will be accepted by the public or fall victim to growing polarization in perceptions and positions.
Extensive research on gender and politics indicates that women legislators are more likely to serve on committees and sponsor bills related to so-called “women's issues.” However, it remains unclear whether this empirical regularity is driven by district preferences, differences in legislator backgrounds, or because gendered political processes shape and constrain the choices available to women once they are elected. We introduce expansive new data on over 25,000 US state legislators and an empirical strategy to causally isolate the different channels that might explain these gendered differences in legislator behavior. After accounting for district preferences with a difference-in-differences design and for candidate backgrounds via campaign fundraising data, we find that women are still more likely to serve on women's issues committees, although the gender gap in bill sponsorship decreases. These results shed new light on the mechanisms that lead men and women to focus on different policy areas as legislators.
Asian economies are attempting to (re)balance their interests in fostering burgeoning outbound investment and attracting inbound investment, while preserving appropriate regulatory autonomy, while maintaining an attractive environment for foreign investors. To understand the issues and the likely future trajectory for international investment law in the region, this chapter first introduces Poulsen’s comprehensive recent study focusing on the experiences of developing countries world-wide, but including analyses of several Asian states (as outlined in Part 2 below). Despite marshalling powerful arguments and evidence for manifestations of ‘bounded rationality’ in BIT negotiations and drafting, some limits to his theory are suggested by a closer analysis of several countries in the region (Part 3). Given such historical experiences, it seems premature to abandon altogether the current treaty protection regime. Nonetheless, a combination of new approaches is worth considering under existing treaties, including more principled use of proportionality testing and deference to host state decision-making (Part 4.1). Greater care is also needed when assessing the net benefits from entering into new treaties, including the latest research into whether investor-state dispute settlement provisions lead to significantly greater cross-border investment (Part 4.2).
Using daily data on vaccinations, disease spread and measures of social interaction from Google Mobility reports aggregated at the country level for 112 countries, we present estimates of behavioural responses to the global rollout of COVID-19 vaccines. We first estimate correlates of the timing and intensity of the vaccination rollout, finding that countries which vaccinated more of their population earlier strongly tended to be richer, whereas measures of the state of pandemic or its death toll up to the time of the initial vaccine rollout had little predictive ability after controlling for income. Estimates of models of social distancing and disease spread suggest that countries which vaccinated more quickly also experienced decreases in some measures of social distancing, yet also lower incidence of disease, and in these countries, policy-makers relaxed social distancing measures relative to countries which rolled out vaccinations more slowly.
Chapter 4 analyzes Tinbergen’s scientific coming of age under the mentorship of the physicist Paul Ehrenfest. Tinbergen started his studies in mathematics and physics in 1921 in Leiden where he encountered some of the leading physicists of the age, such as Heike Kamerlingh Onnes and Ehrenfest. Especially the latter helped turned Leiden into a lively scientific hub with innovations in the curriculum, teaching methods, and his famous inquisitive seminars, which earned Ehrenfest the title the Socrates of Leiden. From 1923 onward Tinbergen was mentored by Ehrenfest, who guided his studies in both physics and economics. The chapter details the difficult choice that Tinbergen had to make between these two fields, as well as the shared vision that Tinbergen and Ehrenfest developed about the role of science and scientists in modern society. In 1929 Tinbergen completed his dissertation in physics, which already contained some analogies between physical and economic phenomena. In the following years Ehrenfest stimulated Tinbergen’s statistical research in economics, which soon became part of the new field of econometrics. The two would host the meetings of the Econometric Society in 1933, but just days before, Ehrenfest would take his own life.
Chapter 6 analyzes the trajectory from his early econometric studies to the macroeconomic model he completed in 1936. During this period, he worked at the Central Bureau of Statistics and the Netherlands Economics Institute, to develop new methods to study business cycles. That research was linked to a network of similar institutes across Europe in London, Vienna, Paris, Berlin, and beyond. The chapter demonstrates how the analysis of the dynamics of particular markets provided inspiration for a study of the dynamics of the overall economy. The goal shared by many theorists of the age was to arrive at a dynamic economic theory, as opposed to the static equilibrium models of classical economics. Tinbergen sought to identify the relevant mechanism that could explain the type of movements typically seen in the overall economy: business cycles of about eight years. But the chapter argues that there was also an iterative dynamic between the political and policy issues of the time and Tinbergen’s work, which was never purely scientific or disconnected from practical concerns. The chapter concludes with a sketch of the main characteristics of his econometric work: the dynamic nature, the combination between theory and empirics, the substantive institutional emphasis, and the way in which Tinbergen believed that quantitative econometric studies could help overcome theoretical and political differences.
Building on the success of Abadir and Magnus' Matrix Algebra in the Econometric Exercises Series, Statistics serves as a bridge between elementary and specialized statistics. Professors Abadir, Heijmans, and Magnus freely use matrix algebra to cover intermediate to advanced material. Each chapter contains a general introduction, followed by a series of connected exercises which build up knowledge systematically. The characteristic feature of the book (and indeed the series) is that all exercises are fully solved. The authors present many new proofs of established results, along with new results, often involving shortcuts that resort to statistical conditioning arguments.
Increasing prevalence of overweight and obese people in England has led policymakers to consider regulating the use of price promotions on foods high in fat, sugar and salt content. In January 2019, the government opened a consultation programme for a policy proposal that significantly restricts the use of price promotions that can induce consumers to buy higher volumes of unhealthy foods and beverages. These proposed policies are the first of their kind in public health and are believed to reduce excess purchasing and, therefore, overconsumption of unhealthy products. This study summarises evidence relating price promotions to the purchasing of food and drink for home consumption and places it in the context of the proposed policy.
Design:
Non-systematic review of quantitative analyses of price promotions in food and drink published in peer-reviewed journals and sighted by PubMed, ScienceDirect & EBSCOhost between 1980 and January 2018.
Results:
While the impact of price promotions on sales has been of interest to marketing academics for a long time with modelling studies showing that its use has increased food and drink sales by 12–43 %, it is only now being picked up in the public health sphere. However, existing evidence does not consider the effects of removing or restricting the use of price promotions across the food sector. In this commentary, we discuss existing evidence, how it deals with the complexity of shoppers’ behaviour in reacting to price promotions on foods and, importantly, what can be learned from it in this policy context.
Conclusions:
The current evidence base supports the notion that price promotions increase purchasing of unhealthy food, and while the proposed restriction policy is yet to be evaluated for consumption and health effects, there is arguably sufficient evidence to proceed. This evidence is not restricted to volume-based promotions. Close monitoring and proper evaluation should follow to provide empirical evidence of its intended and unintended effects.
In the framework of a critical illustration of the contemporary history of economics, this chapter considers applied economics, econometrics, input–output analysis, descriptive statistics and statistical indicators, the theory of market regulation, market creation and auctions, the variegated history of energy economics from the Hotelling theorem to trilateral oligopoly and the Malthusian Club of Rome thesis of resource scarcity, the different approaches to environmental economics.
Mixed-methods designs, especially those in which case selection is regression-based, have become popular across the social sciences. In this paper, we highlight why tools from spatial analysis—which have largely been overlooked in the mixed-methods literature—can be used for case selection and be particularly fruitful for theory development. We discuss two tools for integrating quantitative and qualitative analysis: (1) spatial autocorrelation in the outcome of interest; and (2) spatial autocorrelation in the residuals of a regression model. The case selection strategies presented here enable scholars to systematically use geography to learn more about their data and select cases that help identify scope conditions, evaluate the appropriate unit or level of analysis, examine causal mechanisms, and uncover previously omitted variables.