Economic Cycle and Bank Liquidity Hoarding: Are They Procyclical or Countercyclical?

The paper empirically examines bank liquidity hoarding fluctuations over the economic cycle and provides further evidence on the heterogeneous cyclicality of bank liquidity hoarding across different banks in Vietnam for the period 2007–2019. Using both static panel models with the fixed-effects regression using corrected Driscoll-Kraay standard errors and dynamic panel models with the two-step system generalized method of moments estimator, we find that the liquidity hoarding of banks is procyclical. Concretely bank liquidity hoarding on- and off-balance sheets tends to increase during economic upturns and decrease during economic downturns. Our additional analysis yields a consistent pattern that financially weaker banks are more procyclical than their stronger counterparts. During booms and busts, the behaviour of hoarding liquidity is more pronounced for banks with smaller sizes, less capital, more risk, and less profit. This heterogeneity also contributes to understanding the core mechanism behind our main findings, further confirming the precautionary motive of bank liquidity hoarding.

Bayesian Analysis of Partially Linear Additive Spatial Autoregressive Models with Free-Knot Splines

This article deals with symmetrical data that can be modelled based on Gaussian distribution. We consider a class of partially linear additive spatial autoregressive (PLASAR) models for spatial data. We develop a Bayesian free-knot splines approach to approximate the nonparametric functions. It can be performed to facilitate efficient Markov chain Monte Carlo (MCMC) tools to design a Gibbs sampler to explore the full conditional posterior distributions and analyze the PLASAR models. In order to acquire a rapidly-convergent algorithm, a modified Bayesian free-knot splines approach incorporated with powerful MCMC techniques is employed. The Bayesian estimator (BE) method is more computationally efficient than the generalized method of moments estimator (GMME) and thus capable of handling large scales of spatial data. The performance of the PLASAR model and methodology is illustrated by a simulation, and the model is used to analyze a Sydney real estate dataset.

Productivity and Efficiency in European Milk Production: Can We Observe the Effects of Abolishing Milk Quotas?

The study aims to explore the sources of competitiveness of dairy producers before and after the abolition of milk quotas in selected EU member states. The investigation is based on the stochastic frontier modelling of an input distance function in the specification of the four-error-component model. The model is estimated with a multistep procedure employing the generalized method of moments estimator, addressing the potential endogeneity of netputs, and panel data gained from the FADN database. The results revealed that total factor productivity experienced an increasing trend in the majority of the analysed countries. Since the main driver of productivity growth was found to be the scale effect, our findings support the hypothesis that abolishing milk quotas has a positive effect.

Determinants of Bioenergy Consumption in the European Continental Countries: Evidence from GMM Estimation

This study contributes to the existing literature by examining bioenergy consumption and related factors in continental European countries (ECC). This study extends the current research through its focus on the ECC, which mainly consists of nationwide studies. This study analyses the determinants of bioenergy consumption in the ECC from 2005-2013, estimates its economic variables and evaluates the influence of each variable on bioenergy consumption and related significance level. A generalised method of moments estimator (GMM) was designed for ECC. The estimated models show that bioenergy capital input (CI) positively impacts bioenergy consumption. The most influential factor on use was the price of bioenergy (PR) followed by investment (INV), then gross domestic product (GDP). These results should be considered and used as a tool to develop legislation and policies that could benefit the bioenergy sector in ECC. The evidence shows that CI, INV, and PR have been the primary keys in improving bioenergy consumption in recent years in ECC countries. Thus, they have advanced the efficiency of bioenergy consumption.

EFFECTS OF RENT-SEEKING ON ECONOMIC GROWTH IN LOW-INCOME ECONOMIES

Sluggish growth in low-income countries, despite the high performance in other economic indicators, motivates the literature to switch attention to institutions. Despite its crucial economic implications, there is limited attention on rent-seeking as a driver of economic growth in low-income countries. This paper investigates the effect of rent-seeking on growth in low-income countries from 2004 to 2017using the system generalized method of moments estimator. The empirical results reveal that rent-seeking negatively affects growth, implying that it obstructs the pace of economic development in low-income countries. Hence, it is necessary for policymakers in these countries to adopt anti-rent-seeking policies to promote a rapid and sustainable growth.

Performance measurement of ESG-themed megatrend investments in global equity markets using pure factor portfolios methodology

ESG factors are becoming mainstream in portfolio investment strategies, attracting increasing fund inflows from investors who are aligning their investment values to Sustainable Development Goals (SDG) declared by the United Nations Principles for Responsible Investments. Do investors sacrifice return for pursuing ESG-aligned megatrend goals? The study analyses the risk-adjusted financial performance of ESG-themed megatrend investment strategies in global equity markets. The analysis covers nine themes for the period 2015–2019: environmental megatrends covering energy efficiency, food security, and water scarcity; social megatrends covering ageing, millennials, and urbanisation; governance megatrends covered by cybersecurity, disruptive technologies, and robotics. We construct megatrend factor portfolios based on signalling theory and formulate a novel measure for stock megatrend exposure (MTE), based on the relative fund flows into the corresponding thematic ETFs. We apply pure factor portfolios methodology based on constrained WLS cross-sectional regressions to calculate Fama-French factor returns. Time-series regression rests on the generalised method of moments estimator (GMM) that uses robust distance instruments. Our findings show that each environmental megatrend, as well as the disruptive technologies megatrend, yielded positive and significant alphas relative to the passive strategy, although this outperformance becomes statistically insignificant in the Fama-French 5-factor model context. The important result is that most of the megatrend factor portfolios yielded significant non-negative alphas; which supports our assumption that megatrend investing strategy promotes SDGs while not sacrificing returns, even when accounting for transaction costs up to 50bps/annum. Higher transaction costs, as is the case for some of these ETFs with expense ratios reaching 80-100bps, may be an indication of two things: ESG-themed megatrend investors were willing to sacrifice ca. 30-50bps of annual return to remain aligned with sustainability targets, or that expense ratio may well decline in the future.

Using information from singletons in fixed-effects estimation: xtfesing

In this article, we describe the xtfesing command. The command implements a generalized method of moments estimator that allows exploiting singleton information in fixed-effects panel-data regression as in Bruno, Magazzini, and Stampini (2020, Economics Letters 186: Article 108519).

Is the effect of board diversity on CSR diverse? New insights from one-tier vs two-tier corporate board models

Purpose The purpose of this study is to investigate the impact of board diversity on corporate social responsibility (CSR). The aim is twofold; does board diversity has any effect on CSR, do structural and demographic differences between one-tier and two-tier board models may impact this effect? Design/methodology/approach This paper applies a panel generalized method of moments estimator to a sample of 2,544 non-financial listed firms from 42 countries over the period of 2013–2017. Findings The findings reveal that board diversity leads to effective CSR. By distinguishing between diversity among boards from diversity within boards, the results display the effects of the specific variables that make up the manner and latter’s constructs within unitary and two-tier board structures. Specifically, this paper reveals that tenure, ideology and educational level (gender and nationality) predominantly appear to drive a firm’s CSR within one (two)-tier boards settings. These results remain consistent when robustness tests are ruled. Practical implications The study provides managers, investors and policymakers with knowledge about how among and within board diversity attributes favor the decision-making process around CSR. The evidence is useful for companies in setting the criteria to identify directors who can support their strategic decisions. It benefits, moreover, academics in better understanding firms’ CSR determinants and practices under different corporate board models. Social implications Examining how different sets of board diversity affect firms’ CSR given divergences between one-tier and two-tier board structure is a useful and informative endeavor for all community actors. Originality/value Unlike prior studies that identify the limited scope of diversity, the study is the first to examine the effect of broader dimensions of board diversity on CSR under both one-tier and two-tier board settings. This paper provides a contribution to a greater understanding of the impacts underlying board models and different attributes of board diversity on CSR. This new understanding will help to improve predictions of different features of board diversity impacts on decision-making processes around organizational outcomes.

NON-PERFORMING LOANS, CAPITAL ADEQUACY, LOAN LOSS PROVISION, AND BANK PROFITABILITY: A CASE OF LICENSED GHANAIAN BANKS

This article explored the affiliation between a non-performing loan, capital adequacy ratio, loan loss provision, and bank profitability. The study was conducted on the licensed commercial banks in Ghana for the era 2014-2019. The two-step system generalized method of moments estimator was utilized to test the hypothesis developed for the study. The independent study variables altogether demonstrated a negative and immaterial association with the bank's profitability as proxied by ROA. A robustness test was conducted utilizing the Three-Stage Least-Squares Regression (3SLS); the outcome was analogous to that of the Two-Step System Generalized Method of Moments estimator. The study suggests that the Central Bank fortifies the capital requirement and keenly monitors banks' risk-taking conduct and banks undertaking due diligence procedures to moderate the shock of non-performing loans and loan loss provision in other to augment the profitability of universal banks. KEYWORDS: Non-Performing Loans, Capital Adequacy, Loan Loss Provision, Bank Profitability, GMM JEL Codes: E58, G21, G32