Research

Abstract: The classifications of inflationary regimes proposed in the literature have mostly been based on arbitrary characterizations, subject to value judgments by researchers. We propose a new methodological approach that reduces subjectivity and improves accuracy in constructing such regimes. Our method combines clustering techniques and classification trees to enable the historical periodization of Argentina's inflationary history from 1943 to 2022. Furthermore, we introduce two procedures to smooth out the classification over time: a measure of temporal contiguity of observations and a rolling method based on the simple majority rule. We compare the obtained regimes against existing literature on the inflation-relative price variability relationship, demonstrating the superior performance of our proposed regimes.

Abstract: In this paper we investigate the performance of five causality-detection methods and how their results can be aggregated when multiple units are considered in a panel data setting. The aggregation procedure employs voting rules for determining which causal paths are identified for the sample population. Using simulated and real-world panel data, we show the performance of this methods in detecting the correct causal paths in comparison to a benchmark that comprises a standard representation of growth processes as ground truth model. We find that the results may be better when only simulated, instead of real-world, data are analyzed. While this may suggest that the methods presented here are are currently incapable of detecting causal links, it is plausible that the ground "truth'' may incorporate false relations.

Abstract: This paper explores the heterogeneity of causal structures of economic growth among countries by proposing a two-step procedure. First, we apply a causal discovery technique to uncover the underlying causal structure for each country. Second, we employ hierarchical clustering over these estimates to identify groups of similar countries in terms of their causal relationships. We obtain five “causality clubs”, each one associated with a different structure of causal determinations of the growth process. We find that the usual associations between income or geographical location and the nature of economic growth processes may not always hold true.

Abstract: The volatile and upward behavior of beef prices above the general price level led the Argentine government to implement export restrictions in May 2021 to stabilize domestic prices. This paper employs the synthetic control method to assess the impact of this policy on retail beef prices in the city of Bahía Blanca, Argentina. The results indicate a temporary effectiveness of the intervention in terms of price stabilization, causing a slowdown in beef prices between July and October 2021 that would not have otherwise occurred.