This paper analyzes how interaction effects can be consistently estimated under economically plausible assumptions in linear panel models with a fixed Tdimension. We advocate for a correlated interaction term estimator (CITE) and show that it is consistent under conditions that are not...

Regressors often have heterogeneous effects in the social sciences, implying unit-specific slopes. OLS is frequently applied to these correlated coefficient models. I first show that without restrictions on the relation between slopes and regressors, OLS estimates can take any value including...

This paper takes a deep dive into mesh routing protocols, unraveling how they hold up under the pressures of varying node densities and the hustle and bustle of mobility. This paper included robust and advanced non-parametric statistical tests-think Kruskal-Wallis and Mann-Whitney-to figure out...

Regulation 2016/427 (later consolidated in Regulation 2017/1151) introduced light-duty vehicle on road testing in addition to the laboratory tests for the type approval of vehicles in the European Union. Since then, vehicle emissions have been extensively measured with different types of...

Machine learning applications in finance commonly employ feature decorrelation techniques developed for generic statistical problems. We investigate whether this practice appropriately addresses the unique characteristics of financial data, where correlations often encode fundamental economic...

Different methods of eliciting long-run expectations yield data that predict economic choices differently well. We ask members of a wide population sample to make a 10-year investment decision and to forecast stock market returns in one of two formats: they either predict the average of annual...

Different methods of eliciting long-run expectations yield data that predict economic choices differently well. We ask members of a wide population sample to make a 10-year investment decision and to forecast stock market returns in one of two formats: they ei- ther predict the average of annual...

The presence of autocorrelated financial returns has major implications for investment decisions. Unsurprisingly, therefore, numerous studies have sought to shed light on whether returns are autocorrelated or not, to what extent, and when. Standard tests for autocorrelation rely on the...

This study examines the evolution of public debt among the 27 EU member states using Graph Theory tools; the Threshold Weighted-Minimum Dominating Set (TW-MDS) and the k-core decomposition method, alongside a standard network quantitative metric, the density. By separating the data into three...

The paper introduces a new type of shrinkage estimation that is not based on asymptotic optimality but uses artificial intelligence (AI) techniques to shrink the sample eigenvalues. The proposed AI Shrinkage estimator applies to both linear and nonlinear shrinkage, demonstrating improved...

This research employs Multifractal Detrended Fluctuation Analysis (MFDFA) to investigate multifractal properties in financial variables, including Bitcoin prices and economic indicators. Spanning 2019-2022, the analysis reveals multifractal scaling not only in Bitcoin prices, but also in...

We argue that capital misallocation arises endogenously due to incomplete consumption insurance. We model risk-averse entrepreneurs with heterogeneous productivity who face idiosyncratic output shocks and choose how much capital to rent before uncertainty unfolds. We show that incomplete markets...

Since China implemented its carbon trading mechanism, trading risks arising from unstable carbon prices have significantly reduced its emission-reduction efficiency. Unlike traditional research, which focuses on the impact of fossil fuels on carbon prices, this study emphasises risk spillovers...

We examine and test the environmental performance of family firms across 22 European countries and find that they exhibit better environmental performance than nonfamily firms. This result confirms prior research conducted in the United States. More specifically, we conclude that family firms...

In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data, taking the logarithm of the squared returns to obtain a linear state space model. A well-known series representation links the correlations between elements of the observation...

We devise two algorithms for approximating solutions of PSDisation, a problem in actuarial science and finance, to find the nearest valid correlation matrix that is positive semidefinite (PSD). The first method converts the PSDisation problem with a positive semidefinite constraint and other...

We investigate linkages between three different markets: renewable energy (represented by a range of renewable energy ETFs); traditional energy (represented by crude oil ETF); and common stocks (represented by the S&P 500 Index ETF). We use daily data from 2008 to 2021. The econometric framework...

In the last few decades, the study of ordinal data in which the variable of interest is not exactly observed but only known to be in a specific ordinal category has become important. In Psychometrics such variables are analysed under the heading of item response models (IRM). In Econometrics,...

The price of cryptocurrency Bitcoin has risen sharply over the past ten years, with many investors adding Bitcoin to their portfolios, benefitting from price increases and diversifying their investments. But is Bitcoin suitable for this purpose? This Weekly Report examines the extent to which...

The popular Wishart (WI) processes, first introduced by Bru in 1991, exhibit convenient analytical properties for modeling asset prices, particularly a closed-form characteristic function, and the ability to jointly model stochastic volatility and correlation. These features tend to increase...

There has been growing interest among investors to include cryptocurrencies in their portfolios because of their diversification potential. However, the diversification role of cryptocurrencies when added to South African bank equities is yet to be determined. This study rigorously evaluates...

This paper examines the extent of stock-returns' co-movements among firms in different countries and explores how various measures of closeness affect those co-movements by estimating a spatial autoregressive (SAR) convex combination model that merges four weight matrices-geographical distance,...

Amid the growing debate over how cryptocurrencies are reshaping global finance, this study explores the nexus between Bitcoin, Brent Crude Oil, Gold and the U.S. Dollar Index. We used a time-varying vector autoregressive (tvVAR) model to examine the connection among these four assets during the...