We propose the double robust Lagrange multiplier (DRLM) statistic for testing hypotheses specified on the minimizer of the population continuous updating objective function. The (bounding) χ2 limiting distribution of the DRLM statistic is robust to both misspecification and weak identification,...

We offer a contribution to the analysis of optimal monetary policy. The standard approach to determine what policy rule a central bank should follow is to take a single structural model and minimize the unconditional volatilities of inflation and real activity. In this paper, we propose monetary...

This paper investigates how different parametrisations of the monetary policy reaction function and different mechanisms of expectation formation shape the macroeconomic outcomes in the estimated Smets-Wouters type of DSGE model. The initial macroeconomic conditions of the simulations correspond...

Agent-Based Models (ABMs) provide powerful tools for economic analysis, capturing microto-macro interactions and emergent properties. However, integration with empirical data has been a persistent challenge. To address it, we propose a protocol for integration between empirical data and ABM,...

This short paper explains the theory of path dependence and clarifies its relation to concepts such as positive feedback or lock-in, arguing that path dependence is a core theoretical element of political economy in general, and institutional and evolutionary economics in particular. We first...

This short paper explains the theory of path dependence and clarifies its relation to concepts such as positive feedback or lock-in, arguing that path dependence is a core theoretical element of political economy in general, and institutional and evolutionary economics in particular. We first...

Energy system models are important tools to guide our understanding of current and future carbon dioxide emissions as well as to inform strategies for emissions reduction. These models offer a vital evidence base that increasingly underpins energy and climate policies in many countries. In light...

We investigate the emergence of momentum and reversal anomalies in a general equilibrium model with complete markets and cognitively biased agents, accounting for the presence of representativeness heuristic, conservatism, and anchoring and adjusting in their beliefs. We characterize anomalies...

In this paper, we develop an autoregressive process of order one, assuming that the innovation random variable has a Lindley distribution. The key properties of the process are investigated. Five distinct estimation techniques are used to estimate the parameters and simulation studies are...

Dieses Gutachten dokumentiert die wichtigsten Ergebnisse zum Effizienzvergleich der deutschen Verteilernetzbetreiber Strom der vierten Regulierungsperiode. Das gewählte Effizienzvergleichsmodell besteht aus Messlokationen, Netzlängen auf den Spannungsebenen, Jahreshöchstlasten auf den...

This paper proposes an information-based inference method for partially identified parameters in incomplete models that is valid both when the model is correctly specified and when it is misspecified. Key features of the method are: (i) it is based on minimizing a suitably defined...

A mutualism of nature-inspired algorithms, the Bald Eagle Search Algorithm (BESA) with the Crow Search Algorithm (CSA), is proposed for Gaussian Mixture Model optimisation in the speaker verification framework. BESA simulates bald eagles' hunting behaviour, whereas CSA simulates crows'...

In many set-identified models, it is difficult to obtain a tractable characterization of the identified set. Therefore, researchers often rely on nonsharp identification conditions, and empirical results are often based on an outer set of the identified set. This practice is often viewed as...

Evaluating policy in imperfectly competitive markets requires understanding firm behavior. While researchers test conduct via model selection and assessment, we present the advantages of Rivers and Vuong (2002) (RV) model selection under misspecification. However, degeneracy of RV invalidates...

Modeling policy effects in the context of high-dimensional data requires a balanced consideration of omitted interaction bias and overfitting problems. This paper investigates the role of machine learning algorithms in stabilizing estimates and demonstrates the possible regularization bias...

This paper develops the nonparametric identification of models with production complementarities, worker-firm specific disutility of labor and search frictions. Mobility in the model is subject to preference shocks, and we assume that firms can write wage contracts. We develop a constructive...

Modeling of non-carbon dioxide (non-CO2) greenhouse gas (GHG) emissions in integrated assessment models (IAMs) is critical to achieving long-term climate targets. This study selects nine IAMs to reveal the modeling mechanisms and mitigation of non-CO2 GHGs. It further explores the impact of...

The Danish fire loss dataset records commercial fire losses under three insurance coverages: building, contents, and profits. Existing research has primarily focused on the heavy-tail behaviour of the losses but ignored the relationship among different insurance coverages. In this paper, we aim...

Empirical research typically involves a robustness-efficiency tradeoff. A researcher seeking to estimate a scalar parameter can invoke strong assumptions to motivate a restricted estimator that is precise but may be heavily biased, or they can relax some of these assumptions to motivate a more...

Identification based on higher moments has drawn increasing theoretical attention and been widely adopted in empirical practice in macroeconometrics in the last two decades. This article reviews two parallel strands of the literature: identification strategies based on heteroskedasticity and...