Sustained efforts and investments in different sectors are essential for the overall development of a region. Various studies around the globe underscore the importance of investment in road transport infrastructure in many developing countries to achieve their development targets. The...

This paper focuses on an empirical analysis of the relationship between investing and saving, taking into account various economic regions. The economic aggregates are selected following the International Monetary Fund (IMF) standard classification. The investigation is developed within the...

In emerging markets, stock markets play a crucial role in supporting long-term growth. This study explores the causal relationship between stock market development and economic growth in the Fragile Five countries-Brazil, India, Indonesia, South Africa, and Turkey-covering the period from 2001...

This paper presents a novel method for estimating treatment effects in cases where prior knowledge of the exogeneity of the treatment variable is limited. We employ a machine learning technique, double selection via Lasso, to identify a robust set of control variables without requiring prior...

Applied researchers commonly interpret coefficient movements across OLS and difference-in-differences specifications with varying controls as evidence of bias reduction or improved identification. This note shows that such interpretations generally fail under heterogeneous treatment effects. In...

Banks often assume that higher credit limits increase customer default risk because greater exposure appears to imply greater vulnerability. This reasoning, however, conflates correlation with causation. Whether increasing a customer's credit limit truly raises the likelihood of default remains...

Researchers typically collect experimental data sequentially, allowing early outcome observations and adaptive treatment assignment to reduce exposure to inferior treatments. This article reviews multi-armed-bandit adaptive experimental designs that balance exploration and exploitation. Because...

Researchers typically collect experimental data sequentially, allowing early outcome observations and adaptive treatment assignment to reduce exposure to inferior treatments. This article reviews multiarmed-bandit adaptive experimental designs that balance exploration and exploitation. Because...

This paper provides an introduction to Double/Debiased Machine Learning (DML). DML is a general approach to performing inference about a target parameter in the presence of nuisance functions: objects that are needed to identify the target parameter but are not of primary interest. Nuisance...

We approximate the finite-sample distribution of impulse response function (IRF) estimators that are just-identified with a weak instrument using the conventional local-to-zero asymptotic framework. Since the distribution lacks a mean, we assess bias using the mode and conclude that researchers...

We study firms' financial and real decisions after an exogenous change in their interest rate beliefs induced by a survey experiment with an information treatment. Firms revise their expectations downward after learning about the European Central Bank's policy rate. Moreover, we find a reduction...

We investigate the long-run relationship between organized crime and corruption using data from 20 Italian regions over 30 years. As Rose-Ackerman and Palifka (2018) argue, corruption and organized crime often go together. Our study contributes to the literature in several ways in terms of...

Many instrumental variables applications specify a single Bernoulli treatment. But instruments may change outcomes through multiple pathways or by varying treatment intensity. Lottery instruments that boost charter school enrollment, for instance, may affect outcomes by lengthening time enrolled...

This paper proposes a new resilience index, CLARE (Causal machine Learning Approach to Resilience Estimation), which is rooted in an impact evaluation framework and causal machine learning algorithms applied to longitudinal household survey data. The indicator is model-agnostic, data-driven,...

Global warming remains one of the greatest threats to the sustainability of the planet. The literature is replete with studies investigating the economic effects of global warming with very little attention being paid to the financial ramifications. To this end, the present study attempts to...

We estimate monetary wage returns to academic-track education, Germany’s elite secondary school type granting university entrance. Because academic-track attendance and subsequent university education are institutionally linked, we disentangle their contributions using a causal mediation...

This study addresses a fundamental challenge in the empirical application of the Capability Approach: the measurement of the "capability set" as an opportunity set. Unlike standard utility-based measures that focus solely on achieved outcomes, measuring capability requires assessing the welfare...

Building on the testable implications for IV validity underlying local average treatment effect (LATE) estimation, we (i) propose a simple testing procedure that may accommodate high-dimensional covariates and (ii) demonstrate that it can also detect biases arising from misspecified IV...

When multiple instruments are available, conventional instrumental variable estimators aggregate across potentially heterogeneous margins of compliance and may yield effects that lack a clear economic interpretation. The problem is compounded when some instruments violate the exclusion...

Design-based econometrics, centred on average treatment effects in the potential-outcomes framework, treats causal effects as population-level expectations under hypothetical interventions and thereby offers an expectation-based, mechanism-agnostic conception of causality. This conception is...

This paper investigates the nexus between medium- and high-technology exports and electric- ity consumption from 2016M1 to 2025M05 in Turkey. Nonlinear features in the data lead the use of a Smooth Transition Regression model that shows entrepreneurial expansion which intensifies electricity...

Intensive care units (ICUs) operate with fixed capacities and face uncertainty such as demand variability, leading to demand-driven, early discharges to free up beds. These discharges can increase ICU readmission rates, negatively impacting patient outcomes and aggravating ICU bottleneck...

This study rigorously examines the causality between banking development, economic growth, and income inequality using annual panel data for 13 Central Eastern European transition economies from 2000 to 2020. The Granger non-causality test of heterogeneous panels based on the Toda and Yamamoto...

The changing geopolitical situation in the European region has actualized the issues of further EU enlargement. As a result, the relevance of studying many aspects of the functioning economic systems of candidate countries has increased. In this context, the purpose of this article is to...

This study investigates the impact of economic policy uncertainty (EPU) on macro price divergence in China. We use the time-varying parameter vector auto regressive model with latent thresholds (LT-TVP-VAR) to examine the nonlinear causality relationship. Our findings suggest when the EPU rises,...

We study the interaction of education in adolescence and labor force participation around retirement age and its effect on cognitive abilities for individuals in Europe. Besides a direct long-run effect of education, indirect ones may arise, specifically through labor force participation. We...