• Using instrumental variables to establish causality

    Even with observational data, causality can be recovered with the help of instrumental variables estimation

    Sascha O. Becker, April 2016
    Randomized control trials are often considered the gold standard to establish causality. However, in many policy-relevant situations, these trials are not possible. Instrumental variables affect the outcome only via a specific treatment; as such, they allow for the estimation of a causal effect. However, finding valid instruments is difficult. Moreover, instrumental variables estimates recover a causal effect only for a specific part of the population. While those limitations are important, the objective of establishing causality remains; and instrumental variables are an important econometric tool to achieve this objective.
  • Measuring employment and unemployment

    Should statistical criteria for measuring employment and unemployment be re-examined?

    Measuring employment and unemployment is essential for economic policy. Internationally agreed measures (e.g. headcount employment and unemployment rates based on standard definitions) enhance comparability across time and space, but changes in real labor markets and policy agendas challenge these traditional conventions. Boundaries between different labor market states are blurred, complicating identification. Individual experiences in each state may vary considerably, highlighting the importance of how each employed or unemployed person is weighted in statistical indices.
  • Measuring the cost of children

    Knowing the real cost of children is important for crafting better
 economic policy

    Olivier Donni, March 2015
    The cost of children is a critical parameter used in determining many economic policies. For instance, correctly setting the tax deduction for families with children requires assessing the true household cost of children. Evaluating child poverty at the individual level requires making a clear distinction between the share of family resources received by children and that received by parents. The standard ad hoc measures (equivalence scales) used in official publications to measure the cost of children are arbitrary and are not informed by any economic theory. However, economists have developed methods that are grounded in economic theory and can replace ad hoc measures.
  • Meta-regression analysis: Producing credible estimates from diverse evidence

    Meta-regression methods can be used to develop evidence-based policies when the evidence base lacks credibility

    Chris Doucouliagos, November 2016
    Good policy requires reliable scientific knowledge, but there are many obstacles. Most econometric estimates lack adequate statistical power; some estimates cannot be replicated; publication selection bias (the selective reporting of results) is common; and there is wide variation in the evidence base on most policy issues. Meta-regression analysis offers a way to increase statistical power, correct the evidence base for a range of biases, and make sense of the unceasing flow of contradictory econometric estimates. It enables policymakers to develop evidence-based policies even when the initial evidence base lacks credibility.
  • Identifying and measuring economic discrimination

    Using decomposition methods helps measure both the amount and source of economic discrimination between groups

    Sergio Pinheiro Firpo, March 2017
    Differences in wages between men and women, white and black workers, or any two distinct groups are a controversial feature of the labor market, raising concern about discrimination by employers. Decomposition methods shed light on those differences by separating them into: (i) composition effects, which are explained by differences in the distribution of observable variables, e.g. education level; and (ii) structural effects, which are explained by differences in the returns to observable and unobservable variables. Often, a significant structural effect, such as different returns to education, can be indicative of discrimination.
  • Gross domestic product: Are other measures needed?

    GDP summarizes only one aspect of a country’s condition; other measures in addition to GDP would be valuable

    Gross domestic product (GDP) is the key indicator of the health of an economy and can be easily compared across countries. But it has limitations. GDP tells what is going on today, but does not inform about sustainability of growth. It does not measure happiness, so residents can be dissatisfied even when GDP is rising. GDP does not consider environmental factors or reflect what individuals do outside paid employment. It might increase in times of military conflicts and after natural disasters or terrorist acts, as the loss of property is not counted. Hence, complementary measures may help to show a more comprehensive picture of an economy.
  • Big Data in economics

    New sources of data create challenges that may require new skills

    Big Data refers to data sets of much larger size, higher frequency, and often more personalized information. Examples include data collected by smart sensors in homes or aggregation of tweets on Twitter. In small data sets, traditional econometric methods tend to outperform more complex techniques. In large data sets, however, machine learning methods shine. New analytic approaches are needed to make the most of Big Data in economics. Researchers and policymakers should thus pay close attention to recent developments in machine learning techniques if they want to fully take advantage of these new sources of Big Data.
  • Disentangling policy effects into causal channels

    Splitting a policy intervention’s effect into its causal channels can improve the quality of policy analysis

    Martin Huber, May 2016
    Policy evaluation aims at assessing the causal effect of an intervention (for example job-seeker counseling) on a specific outcome (for example employment). Frequently, the causal channels through which an effect materializes can be important when forming policy advice. For instance, it is essential to know whether counseling affects employment through training programs, sanctions, job search assistance, or other dimensions, in order to design an optimal counseling process. So-called “mediation analysis” is concerned with disentangling causal effects into various causal channels to assess their respective importance.
  • Evaluating the efficiency of public services

    Differences in efficiency in public services can offer clues about good practice

    Geraint Johnes, October 2015
    Efficiency is an important consideration for those who manage public services. Costs vary with output and with a variety of other factors. In the case of higher education, for example, factors include quality, student demographics, the scale and scope of the higher education provider, and the size and character of the real estate. But even when taking all these factors into account, costs vary across providers because of differences in efficiency. Such differences offer clues about good practice that can lead to improvements in the system as a whole. The role of efficiency is illustrated by reference to higher education institutions in England.
show more