Exchange rate volatility and firm performance in Nigeria: A dynamic panel regression approach

2016 ◽  
Vol 50 (6) ◽  
pp. 161-174
Author(s):  
Ikechukwu Kelilume
Keyword(s):  
Exchange Rate ◽  
Firm Performance ◽  
Exchange Rate Volatility ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Regression Approach ◽  
Dynamic Panel Regression

scholarly journals Do larger boards improve shareholder value creation? – Effects of the board size on business performance in Eastern Central Europe

2020 ◽  
Vol 42 (3) ◽  
pp. 245-279
Author(s):  
Zsolt Lakatos
Keyword(s):  
Firm Performance ◽  
Regression Models ◽  
Positive Impact ◽  
Supervisory Board ◽  
Panel Regression ◽  
Board Size ◽  
Dynamic Panel ◽  
Management Board ◽  
Dynamic Panel Regression ◽  
Panel Regression Models

AbstractThe aim of this study is to analyse the impact of board size on a firms' operational and market performance at the largest East Central European listed non-financial, non-public utility firms. The literature debates the effects of the size of the board. While the resource dependency theory supports a positive effect, the agency theory supports a negative impact on firm value. This question is rarely investigated in two-tiered corporate governance models. This paper estimates the effects of management board and supervisory board size, between 2007 and 2016. The results indicate that the effect of management board size depends heavily on the size of the observed company. In both fixed effects and GMM-type dynamic panel regression models, using Tobin's Q, market-to-book ratio, total shareholder value and ROA as firm performance measures, increase in management board size has a significant positive impact on firm performance; however, in the case of larger firms, the effect is significantly negative. Moreover, the increase in the ratio of outside directors has a positive impact on the firm's performance in all dynamic panel regression models and this effect is even more significant in Tobin's Q and market-to-book ratio models. This can indicate the effective monitoring role of the supervisory board.

scholarly journals Macroeconomic, Institutional and Bank-Specific Determinants of Non-Performing Loans in Emerging Market Economies: A Dynamic Panel Regression Analysis

2019 ◽  
Vol 8 (3) ◽  
pp. 95-110
Author(s):  
Yilmaz Bayar
Keyword(s):  
Regression Analysis ◽  
Banking Sector ◽  
Emerging Market ◽  
Dynamic Panel Data ◽  
Emerging Market Economies ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Market Economies ◽  
Nonperforming Loans ◽  
Dynamic Panel Regression

Abstract Banking sector is important for various macroeconomic and microeconomic variables in terms of mobilization of funds, increasing savings, and providing alternative investment instruments suited to the every person by minimizing the risk of adverse selection and moral hazard, allocating funds to most productive projects, risk diversification. Therefore, sound functioning of the banking sector is critical especially for emerging and developing countries. This study explores the macroeconomic, institutional, and bank-specific factors behind nonperforming banking loans as an indicator of banking sector functioning in emerging market economies over the 2000-2013 period by employing the system GMM dynamic panel data estimator. Results of the dynamic panel regression analysis showed that economic growth, inflation, economic freedom (institutional development), return on assets and equity, regulatory capital to risk-weighted assets, and noninterest income to total income affected nonperforming loans negatively, while unemployment, public debt, credit growth, lagged values of nonperforming loans, cost to income ratio and financial crises affected nonperforming loans positively.

scholarly journals Legal Instruments for Stimulating Interregional Competition for Investment

2020 ◽  
Vol 16 (2) ◽  
pp. 649-665
Author(s):  
V.F. Lapo
Keyword(s):  
Economic Integration ◽  
Driving Force ◽  
Spatial Competition ◽  
Federal District ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Investment Promotion ◽  
Positive Effects ◽  
Economic Interaction ◽  
Dynamic Panel Regression

In order to study the role of legal instruments in stimulating the spatial competition and economic integration of the entities of the Russian Federation, it is necessary to examine a system of interacting regions. Regional laws on investment promotion have been acting and improving for a long time. Thus, the paper examines the set of these laws and their impact on interregional integration and regional competition. The study identifies three levels of competition: the all-Russian competition, competition within federal districts, and competition between neighbouring regions. As benefits as instruments for attracting investments are applied in regions, they influence the decision to invest in other regions. Therefore , the developed econometric mode l of dynamic panel regression of investments assesses the economic interaction between the regions. The model “the dynamic panel regression of investments taking into account the competition between the regions” (DPRI-CR) includes stimulation instruments and spatially weighted variables related to regional benefits. The indicators for assessing regional spatial interaction are based on the coefficients of the similarity of the legal systems in two regions. Testing of the DPRI-CR demonstrates the exiting external positive, negative and neutral effects of investment benefits that significantly differ depending on the level of competition. An increase in the regional economic integration causes an increase in the positive and negative effects. Consequently, the investment policies that are aimed at increasing economic interaction should take into account the region’s economic integration with the economies of the neighbouring regions, regions of the federal district and other entities of the country. The regions, which are closely integrated with the majority of regions, have the most opportunities to use the external effects. They can apply either “driving force of the economy” instruments to enhance positive effects or “driving force of the progress” instruments to increase their competitive position.

Explaining stock market returns in Sub-Saharan Africa using an alternate uncovered interest rate parity framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kofi Bondzie Afful ◽  
William Opoku
Keyword(s):  
Money Supply ◽  
Random Effects ◽  
Stock Markets ◽  
Critical Examination ◽  
Panel Regression ◽  
Market Returns ◽  
Dynamic Panel ◽  
Content Type ◽  
Dynamic Panel Regression ◽  
Sub Saharan

PurposeSub-Saharan African (SSA) stock exchanges are imperfect and inefficient. Therefore, orthodox finance theories are unable to completely explain their market returns. Such models mainly identify anomalies when applied to the sub-region. Consequently, this paper develops an original theoretical model to better explain market returns on the sub-continent.Design/methodology/approachThis paper develops an alternate analytical framework that combines adaptive expectations, Keynesian LM model and modified uncovered interest parity (UIP) formulations to address empirical anomalies identified by previous literature when analyzing SSA's inefficient stock markets. Using panel data, the study first computes the fixed as well as random effects regressions and, later, a Generalized Method of Moments (GMM) dynamic panel regression for further empirical analysis.FindingsBoth the fixed and random effects regression results indicate that the relative output-money supply disparity and foreign inflation-money supply growth rate spread have positive effects on market returns in SSA. On the other hand, foreign interest rates have an inverse effect. Although the GMM dynamic panel regression has similar results, it additionally finds that market returns in SSA are autoregressive. This suggests that past returns are persistent.Research limitations/implicationsA key implication is that multipliers and transmission mechanisms in SSA may take longer to adjust, thereby limiting short-run market returns. Also, policymakers must encourage a critical mass of firms to list in order to enhance efficiency. Additionally, policy variables significantly influence returns. One limitation is the high market segmentation in SSA. This heightens heterogeneity, emphasizing fixed effects.Practical implicationsAlso, the findings of this study may not apply to all emerging economies as SSA economies are highly heterogeneous.Social implicationsThe segmented nature of SSA stock markets may have implications for income inequality and the distribution of resources within the economy. Also, it indicates that there are limits to how firms use capital markets on the sub-continent.Originality/valueThis paper abstracts from the strict ideal market conditions prescribed by modern finance theories and develops an original modified UIP model. It finds that SSA stock markets may be more sensitive to policy variables, instead of determinants postulated by orthodox finance concepts. The study offers opportunities for further critical examination of returns in imperfect frontier markets.

scholarly journals Dynamic Panel Modeling of Climate Change

Econometrics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 30
Author(s):  
Peter C. B. Phillips
Keyword(s):  
Estimation Method ◽  
Practical Implementation ◽  
Model Parameters ◽  
Panel Regression ◽  
Climate Data ◽  
Dynamic Panel ◽  
Panel Regressions ◽  
Regression Parameters ◽  
Dynamic Panel Regression ◽  
Temperature Radiation

We discuss some conceptual and practical issues that arise from the presence of global energy balance effects on station level adjustment mechanisms in dynamic panel regressions with climate data. The paper provides asymptotic analyses, observational data computations, and Monte Carlo simulations to assess the use of various estimation methodologies, including standard dynamic panel regression and cointegration techniques that have been used in earlier research. The findings reveal massive bias in system GMM estimation of the dynamic panel regression parameters, which arise from fixed effect heterogeneity across individual station level observations. Difference GMM and Within Group (WG) estimation have little bias and WG estimation is recommended for practical implementation of dynamic panel regression with highly disaggregated climate data. Intriguingly, from an econometric perspective and importantly for global policy analysis, it is shown that in this model despite the substantial differences between the estimates of the regression model parameters, estimates of global transient climate sensitivity (of temperature to a doubling of atmospheric CO2) are robust to the estimation method employed and to the specific nature of the trending mechanism in global temperature, radiation, and CO2.

scholarly journals Regional disparity of covid-19 infections: an investigation using state-level Indian data

2021 ◽  
Author(s):  
Parantap Basu ◽  
Ritwik Mazumder
Keyword(s):  
Panel Data ◽  
Urban Areas ◽  
Herd Immunity ◽  
State Level ◽  
Panel Regression ◽  
Dynamic Panel ◽  
Health Infrastructure ◽  
The World ◽  
Dynamic Panel Regression ◽  
Indian Data

AbstractUsing the state-level panel data for India, we establish that Covid infections are clustered in more urbanized, and prosperous states. Poverty lowers cases showing evidence of herd immunity of poor which stands in sharp contrast with the developed part of the world. Our dynamic panel regression results indicate that Covid infections are persistent across states and unlocking has aggravated the infections. We also find that richer and more urbanised states with better health infrastructure and governance perform more tests. The policy lesson from this exercise is that the authorities should monitor immunization and Covid protocols in densely populated urban areas.

scholarly journals The impact of foreign exchange movements on Turkish textile sector

2019 ◽  
Vol 70 (03) ◽  
pp. 291-296
Author(s):  
YUSUF KAYA ◽  
GIZEM GÜNAYDIN KARAKAN ◽  
EMILIA VISILEANU
Keyword(s):  
Exchange Rate ◽  
Firm Performance ◽  
Firm Size ◽  
Exchange Rate Volatility ◽  
Geographical Location ◽  
High Tech ◽  
Firm Age ◽  
Negative Effect ◽  
The Impact ◽  
Textile Sector

Due to importance of global supply chain and high-tech exports, importance of new developing markets is gradually increasing. Turkey keeps the strategic importance for textile sector being in the center of Balkans, Asia, Middle East, North Africa, Eastern Europe and Russia. The geographical location allowing trade in the region makes the country much more advantageous than its competitors. However, devaluation and the exchange rate volatility of Turkish Lira in 2018 have been seriously affecting Turkish textile sector. This study aims to determine the impact of exchange rate fluctuation on Turkish textile firms’ performance between the years of 2013 and 2017. Additionally, multiple regression analysis was done in order to investigate the impact of firms’ performance such as firm age and firm size on performance of the textile firms. According to results, it was observed that exchange rate volatility had a negative effect on the firm performance and the firm size had a negative effect on firm performance while the firm age did not have any influence on firms’ performance significantly.

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