Econometric policy evaluation: A critique

A comprehensive evaluation of fiscal policy reforms requires a methodology that simultaneously considers their aggregate impact on the economy as a whole as well as their distributional implications at the individual or household level.

In this paper, we provide a new link between a fiscal microsimulation model and a macro-econometric model and we analyze the impact of the reform of the Italian tax-benefit system occurred in 2022.

The reform is expected to have a first-round cost of about 15 billion euros due to the tax cut and the increase in child related benefits, with a reduction in inequality of around 0.5 percentage points of Gini index. The second-round effects confirm the reduction in inequality and indicate an initial self-financing effect of about 7%. Our estimates support the importance of integrating micro- and macroeconomic insights for a more accurate assessment of the impact of public policies.

This paper examines the dynamic causal effect of financial markets on cryptocurrencies from a return perspective by applying the dynamic asymmetric causality tests. Applying daily data from February 1, 2018, to August 31, 2023, this paper also investigates whether the major events, such as COVID-19 or the categories of cryptocurrency, will alter or intensify the existing relationship. The empirical result shows that the causal relationship for both symmetric and asymmetric, between traditional financial markets and cryptocurrency is cyclical and only significant in the short term; such a result is robust with the examination of the VAR-based Granger causality test in the presence of instabilities. The pandemic does not influence the causal relationship, and the gold price had the most significant causal impact on cryptocurrency portfolio returns, while the fluctuations in the stock market had a negligible influence and the two indices did not have different causal impacts on the different types of cryptocurrencies. Adding cryptocurrencies to portfolios with only traditional financial assets can significantly reduce risk.

This paper argues that certain erroneous premises upon which the mainstream finance paradigm is based are a structural cause of greenwashing. By scrutinizing the metatheoretical hypotheses of this paradigm through a critical realist lens, we aim to show that it rests upon on tacit representations that impose a distorted view of financial ‘knowledge’, financial systems, the Earth System, and society. This ontological bias leads to fallacious research questions, biased methodologies, and has even generated ill-advised policies that are conducive to the financialization of nature. We then put forth that critical realism could offer realistic metatheoretical foundations for the development of a new ecological finance paradigm.

This paper examines the econometric causal model and the interpretation of empirical evidence based on thought experiments that was developed by Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two currently popular causal frameworks: the Neyman–Rubin causal model and the Do-Calculus. The Neyman–Rubin causal model is based on the language of potential outcomes and was largely developed by statisticians. Instead of being based on thought experiments, it takes statistical experiments as its foundation. The Do-Calculus, developed by Judea Pearl and co-authors, relies on Directed Acyclic Graphs (DAGs) and is a popular causal framework in computer science and applied mathematics. We make the case that economists who uncritically use these frameworks often discard the substantial benefits of the econometric causal model to the detriment of more informative analyses. We illustrate the versatility and capabilities of the econometric framework using causal models developed in economics.

As Richard Day explained, expected utility theory suffers from procedural irrationality. This and other problems are illustrated here in the context of decision-making among low-income farmers. Farmers in developing countries are commonly thought to underinvest in modern techniques because their low incomes make them especially risk averse. In addition to the procedural leap of faith, highly restrictive assumptions are needed to apply expected utility theory to the problem. Nor does expected utility theory, as usually prescribed, fit the narrative of loss aversion. The reader is introduced to a procedurally rational substitute called lexicographic safety first. The model is illustrated for the case of rice fertilization in the Philippines, and policy implications are drawn. To illustrate the potential appeal of lexicographic ordering for other applications involving thresholds, a lexicographic model of rational addiction is also provided.

We examine the process of intertemporal decision-making among potential offenders by analyzing their response to announcements of future changes in anticrime policies. We specify the utility function of potential criminals based on Epstein-Zin preferences to explicitly account for risk attitudes. In this setting, news shocks in anticrime policies can bring about immediate changes in delinquency, but heterogeneous risk attitudes among potential offenders may cause unintended outcomes in the short run. We further show that short-run effects may solidify in the event that the announced policy changes are not ultimately implemented (noise shocks). We demonstrate that rising uncertainty about policy changes may be beneficial in crime prevention, but only among risk-averse agents. Hence, this paper highlights potential pitfalls that result from neglecting the importance of risk attitudes in crime prevention – and potentially other policies.