Effects Panel Data Regression Model Research Articles

Retail traders and co-movement: Evidence from Robinhood trading activity

We find evidence that retail trading activity by Robinhood traders is associated with lower levels of return co-movement and liquidity co-movement. We demonstrate the significance of these relationships primarily employing a two-way fixed effects panel data regression model covering cross-sectional and time-series observations of US stock trades from May 2018 to July 2020. The findings hold true across various cross-sectional subsamples and across subperiods before and after March 2020, coinciding with the stock market crash induced by heightened risks of the COVID-19 pandemic. With regard to returns, our analysis identifies three co-movement channels: 1) increased correlated trading by retail traders, 2) extended delay in incorporating market-wide information, and 3) a direct effect influenced by the integration of firm-specific information into prices. In contrast, for liquidity co-movement, we fail to identify evidence of plausible channels relating to either volatility or correlated trading. However, it appears that the significant direct effects that we document stem from a broadened array of trading strategies when retail traders contribute to the market. Collectively, these findings have important implications as return co-movement limits investors' ability to diversify investments and manage risks, while liquidity co-movement heightens market vulnerability to crashes.

Rank-based max-sum tests for mutual independence of high-dimensional random vectors

We consider the problem of testing mutual independence of high-dimensional random vectors, and propose a series of high-dimensional rank-based max-sum tests, which are suitable for high-dimensional data and can be robust to distribution types of the variables, form of the dependence between variables and the sparsity of correlation coefficients. Further, we demonstrate the application of some representative members of the proposed tests on testing cross-sectional independence of the error vectors under fixed effects panel data regression models. We establish the asymptotic properties of the proposed tests under the null and alternative hypotheses, respectively, and then demonstrate the superiority of the proposed tests through extensive simulations, which suggest that they combine the advantages of both the max-type and sum-type high-dimensional rank-based tests. Finally, a real panel data analysis is performed to illustrate the application of the proposed tests.

Risk Disclosure, Corporate Governance and Firm Value in an Emerging Country

This study aims to examine whether risk disclosure practices and corporate governance mechanisms are associated with the performance of listed companies in Malaysia’s emerging economy. The study uses fixed effects panel data regression models to gauge the relationship using 899 firm-year observations from companies that provide risk disclosures in their annual reports. The findings show that risk disclosure has a significant effect on firm performance. Audit committee monitoring also has a significant relationship with firm performance, while the results regarding the existence of a risk management committee are insignificant. In additional analyses, a composite measure of audit committee effectiveness confirms that its monitoring role improves firm performance significantly. This study addresses risk disclosure practices in an under-researched setting (Malaysia) with different corporate governance models and emerging risk reporting legislation, thus adding to the limited body of knowledge on corporate risk disclosure and corporate monitoring and their impact on firm performance.

Effects of Chinese Equity Ownership and Board Involvement on Firm Profitability: Evidence from Listed Companies in the Malaysian Construction Sector

With 68 countries and international organizations signed up to and participating in the Belt and Road Initiative (BRI), the Chinese business community is playing an increasingly important role in the global economy. The number of Chinese-owned businesses within the top 50 of the Fortune Global 500 list has tripled from four in 2012 to 12 in 2017. With a sample of 24 out of the top 25 market capitalization Malaysian construction sector listed companies from 2012 to 2017, the random effects panel data regression model (REM) is applied. Results reveal that only the percentage of Chinese equity ownership (COWN) and the percentage of Chinese directors on corporate boards (CDIR) have significant relationships with companies’ profitability measure of return on assets (ROA). Chinese CEOs (CCEO) can only improve a company's profitability after two years at the top of the management team. One of the main implications of this research is that COWN and CDIR should not be restricted by the government and indigenous protectionist groups because Chinese equity owners and directors can capitalize on their multi-lingual capabilities to build closer interpersonal ties and networking ("guanxi") with business partners from China and other BRI countries.

The Factors Affecting the Market Value/Book Value and Profitability of REITs in Turkey

Increasing income level and the desire to live a more comfortable life in countries with an increasing population are constantly driving the demand for real estate. Real estate investment trusts (REITs) are capital market institutions that can invest in real estate, real estate-based capital market instruments, real estate projects, real estate-based rights and capital market instruments. In addition, they establish partnerships to realize specific projects, engage in other permitted activities, and are organized by the Capital Market Law in Turkey. In this study, the fixed effects panel data regression model is used to determine the financial indicators that affect the market value and profitability of the Turkey REITs that are traded in the Borsa İstanbul REITs Index. The study covers 21 REIT companies. The data set is in the period between 2010:Q1 to 2019:Q4 in the analyses. The results show that return on assets (ROA), return on equity (ROE), asset turnover, leverage, equity multiplier and current asset turnover are effective on the market to book ratio (MBR). The ratios that affect the ROA are MBR, ROE, acid-test, leverage, equity multiplier, EBITDA/sales and current asset turnover. Moreover, the ratios that affect the ROE are the ROA, MBR, acid-test, asset turnover, leverage, and equity multiplier.

Social networks and household food consumption smoothing in the presence of idiosyncratic shocks: insights from rural Kenya

ABSTRACT Idiosyncratic shocks are among the major shocks affecting smallholder households. Social networks have been widely used by households as an informal strategy to smooth consumption. This article uses panel data from 719 smallholder farmers in Kenya and a fixed effects panel data regression model to evaluate the effect of social networks on food consumption smoothing in the presence of health shocks. Fixed effects estimates show that financial credit networks have a positive and significant effect on insurance of purchased food consumption against health shocks, indicating that the networks play an insurance role against health shocks.

Interest Rate Ceilings and Financial Exclusion in Kenya: Evidence from Commercial Banks’ Sectoral Credit Distribution

The Finance Act that was amended in November 2019 in Kenya saw the removal of the caps on interest charged on loans. The motive of repeal of interest rate caps was to encourage the commercial banks to offer credit to Micro, Small and Medium Enterprises (MSMEs) and other sectors of the economy. The interest rate caps that were implemented in September 2016 led to a significant reduction in lending to the private sector and in particular the small and medium size enterprises and the rural poor which were financially excluded by commercial banks. The main objective of the study was to find out whether interest rate caps contributed to financial exclusion in Kenya’s commercial banks’ sectoral credit portfolio. The target population of the study was 11 private sectors that benefit from commercial banks credit in Kenya. Secondary balanced panel monthly data spanning from January 2016 to December 2019 was used in the study. Fixed effects panel data regression model was used to analyze the data. The results from the study showed a positive and statistically significant relationship between interest rate ceiling and financial exclusion implying that interest rate ceilings affects credit access leading to financial exclusion in Kenya. The results for inflation rate indicated a negative but statistically significant relationship between inflation and financial exclusion implying that inflation affects loan credit growth. The results for exchange rate and public debt are statistically insignificant, suggesting that they do not have an effect on credit access in Kenya’s commercial banks.

Testing for sphericity in a fixed effects panel data model with time-varying variances

This paper proposes a test for the null of sphericity in a fixed effects panel data model with time-varying variances. We construct new test statistics using the within residuals from the fixed effects panel data regression model on the basis of Li and Yao’s (2018) test procedure. We show that the newly proposed test converges to a standard normal distribution as (n,T)→∞ with n∕T→c∈(0,∞). The power properties of the test are studied under both weak and strong factor model alternatives. Monte Carlo simulations are conducted to examine the finite sample performance.

Change of vegetation cover in the US–Mexico border region: illegal activities or climatic variability?

This study explores both human activities and climatic factors to examine the change of vegetation cover in the US Southwest border region—a region that is almost 2000 miles long and with rich natural resources but mostly a sensitive semi-arid/arid ecosystem. It is the first study that integrates large-scale remote-sensing data with multiple layers of socio-economic data and aims to inform critical policy issues related to natural resources management and border security enforcement in the region. A fixed effects panel data regression model is deployed to control for spatial heterogeneities and macro trends in vegetation cover distribution. The results show that both illegal and legal activities have statistically significant impacts on the border region vegetation cover between 2008–2017. Within a 3 mile buffer of the border, a one-standard-deviation increase in illegal border-crossings would lead the vegetation cover index (measured between 0–100) to decline by 4.1% of its standard deviation. A one-standard-deviation increase in border patrol agent staffing would lead the vegetation cover index to decline by 19.0% of its standard deviation. Employment density (a proxy for the dominant local economic activities) in the border county economies and growing season monthly mean temperature are also statistically significant in driving the change of vegetation cover. These findings provide important implications for natural resources management and border security policy in the region, as well as for the quality of life in the local border communities.

Does EVA Beat ROA and ROE in Explaining the Stock Returns in Indian Scenario? An Evidence Using Mixed Effects Panel Data Regression Model

We study a panel data of 1,700 Indian firms listed in either National Stock Exchange (NSE) or Bombay Stock Exchange (BSE) for the period 2001 to 2016 to see if economic value added (EVA) explains the annual stock returns of these Indian firms better than return on assets (ROA) and return on equity (ROE). Using mixed effect model, we find that EVA does explain the annual stock returns of these Indian firms better than ROA and ROE.

The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data

The benefits of cycling have been well established for several decades. It can improve public health and make cities more active and environmentally friendly. Due to the significant net benefits, many local governments in Scotland have promoted cycling. Glasgow City Council constructed four significant pieces of cycling infrastructure between 2013 and 2015, partly in preparation for the 2014 Commonwealth Games and partly to encourage cycling more generally. This required substantial capital investment. However, the effectiveness of these big new infrastructure investments has not been well examined, mostly due to data limitations. In this study, we utilised data from the activity tracking app Strava for the years 2013–2016 and fixed effects panel data regression models to examine whether the new cycling infrastructure has increased cycling volumes on these routes. Our results show that three of the infrastructure projects have a positive effect on the monthly total volume of cycling trips made by users of the app, with flows up by around 12% to 18%. Although this result is promising, it needs to be interpreted with care due to the characteristics of the data.

The Relationship Between Board Diversity and Corporate Financial Performance: <i>Empirical Evidence from Five Selected Commercial Banks in Nigeria</i>

The purpose of this research was to investigate the nature of the relationship between board diversity and financial performance of deposit money Banks quoted on the Nigerian stock exchange. Based on extensive review of the literature, three board diversity variables were identified namely gender (measured by the proportion of women in the boardroom), non-executive directors (measured by the proportion of non-executive directors that make up the boardroom) and board size. Financial performance was measured using Return on Assets (ROA) and Return on Equity (ROE). The Fixed effects Panel data regression model was used to test the nature of relationship between the board diversity variables and the financial performance variables, using secondary data from the Banks annual financial statements covering the period from 2006-2017. The result of the analysis showed that gender diversity has a statistically significant positive impact on banks financial performance. On the other hand, the study also indicated that non-executive directors and board size do not have a significant impact on banks performance. Based on the findings from this study, it was therefore recommended that quoted deposit money banks in Nigeria should raise female proportions in their boardroom so as to improve financial performance.

Financial Stability, Monetary Policy, and Economic Growth: Panel Data Evidence from Developed and Developing Countries

This paper examines the relationship between financial stability, monetary policy, and economic growth in 40 developed and developing countries by using the annual panel data over the period of 1993–2015. Fixed and random effects panel data regression models were fitted to determine the impact of financial stability and monetary policy on economic growth. Our results indicate that trade openness, capital account openness, and foreign direct investment have positive impacts on economic growth with a high degree in developed countries. Our empirical results also indicate a positive and significant impact of research and development on financial development as well as economic growth in developed countries. Financial crises, bank liquid reserves, and bank nonperforming loans affect negatively financial stability, financial development, as well as economic growth. This impact essentially amounts to the sensitivity and fragility of the banking system. In addition, inflation continues to affect economic growth in a negative way. The main findings confirm the complementarity and the importance of real, financial, monetary variables and bank solidity as well their significant impacts on financial stability and economic development.

Improved estimation of fixed effects panel data partially linear models with heteroscedastic errors

Fixed effects panel data regression models are useful tools in econometric and microarray analysis. In this paper, we consider statistical inferences under the setting of fixed effects panel data partially linear regression models with heteroscedastic errors. We find that the usual local polynomial estimator of the error variance function based on residuals is inconsistent, and develop a consistent estimator. Applying this consistent estimator of error variance and spline series approximation of the nonparametric component, we further construct a weighted semiparametric least squares dummy variables estimator for the parametric and nonparametric components. Asymptotic normality of the proposed estimator is derived and its asymptotic covariance matrix estimator is provided. The proposed estimator is shown to be asymptotically more efficient than those ignoring heteroscedasticity. Simulation studies are conducted to demonstrate the finite sample performances of the proposed procedure. As an application, a set of economic data is analyzed by the proposed method.

Modified panel data regression model and its applications to the airline industry: Modeling the load factor of Europe North and Europe Mid Atlantic flights

Abstract This article conducts a stochastic analysis on the passenger load factor of the airline industry. Used to measure competence and performance of the airline, load factor is the percentage of seats filled by revenue passengers. It is considered a complex metric in the airline industry. Thus, it is affected by several dynamic factors. This paper applies advanced stochastic models to obtain the best fitted trend of load factor for Europe's North Atlantic (NA) and Mid Atlantic (MA) flights in the Association of European Airlines. The stochastic model's fit helps to forecast the load factor of flights within these geographical regions and evaluate the airline's demand and capacity management. The paper applies spectral density estimation and dynamic time effects panel data regression models on the monthly load factor flights of NA and MA from 1991 to 2013. The results show that the load factor has both periodic and serial correlations. Consequently, the author acknowledges that the use of an ordinal panel data model is inappropriate for a realistic econometric model of load factor. Therefore, to control the periodic correlation structure, the author modified the existing model was modified by introducing dynamic time effects. Moreover, to eradicate serial correlation, the author applied the Prais–Winsten methodology was applied to fit the model. In this econometric analysis, the study finds that AEA airlines have greater demand and capacity management for both NA and MA flights. In conclusion, this study prosperous in finding an effective and efficient dynamic time effects panel data regression model fit, which empowers engineers to forecast the load factor off AEA airlines.

Stochastic Evaluation of Capacity and Demand Management of the Airline Industry

In the airline industry, the term load factor defined as the percentage of seats filled by revenue passengers and is used to measure efficiency and performance. This metric evaluates the airlines capacity and demand management. This paper applies stochastic models to analyse the load factor of the Association European Airlines (AEA) for flights of Europe - North Africa and Europe- Sub Saharan Africa. The estimation result prevails that the airlines have better demand management in the flights of Europe- Sub Saharan Africa than in the flight of Europe - North Africa. However, the capacity management of the airlines is poor for both regional flights. The autocorrelation structures for the load factor for both regional flights have both periodic and serial correlations. Consequently, the use of ordinal panel data models is inappropriate to capture the necessary variation of the load factor of the regional flights. Therefore, in order to control for the periodic autocorrelation, the author introduces dynamic time effects panel data regression model. Furthermore, in order to eliminate serial correlation the author applies the Prais–Winsten methodology to fit the model. Finally, the author builds realistic and robust forecasting model of the load factor of the Europe- North Africa and Europe-Sub Saharan Africa flights.

The effects of electricity network development besides routine malaria control measures in an underdeveloped region in the pre-elimination phase.

BackgroundThe main purpose of this study was to investigate the effects of electricity network development on malaria transmission. The study was performed in the rural areas of three districts in Sistan-va-Baluchestan Province, Iran.MethodsFrom the mentioned districts, 122 rural communities were selected. The data of the years 2005–2009 were collected retrospectively from data banks of the district health centres and the offices of the local electricity network. Fixed and random effects panel data regression models were fitted to determine the effects of electrification and other variables on malaria transmission during the elimination phase.ResultsIt seems that access to electricity of rural communities, if not harmful, has no obvious effect on malaria control and prevention at least during the elimination phase in an underdeveloped region. Elevation above sea level and precipitation during spring and summer were found to be the other important, respectively, time-invariant and time-dependent variables associated with decreasing and increasing malaria transmission. Indoor residual spraying and the use of insecticide-treated mosquito nets were not found to be effective in decreasing malaria transmission in the elimination phase.ConclusionsThe introduction of electricity to a rural community does not guarantee an absolutely good effect on the reduction of malaria transmission.

Does the crowd matter in refereeing decisions? Evidence from Spanish soccer

This paper analyses referee home bias with data from the First Division of the Spanish Football League between the 2002/03 and 2009/10 seasons. The aim is to assess the behaviour of the referee in relation to two decisions, namely free kicks awarded and players booked. The main contribution of this paper is the way in which it analyses referee bias; free kicks and bookings are not considered independent elements, instead it is presumed that the number of free kicks awarded has an impact on the cards shown. Regarding methodology, two random effects panel-data regression models are estimated. The results obtained do not confirm, at least in the period under analysis, that Spanish soccer referees have been biased in favour of the home team when it comes to awarding free kicks. However, once a free kick has been awarded, there does appear to be a referee home bias in the disciplinary sanctions taken against a player for committing a foul. These findings suggest that when there is a large crowd in the stadium, the referee tends to be more inclined to book away team players than home players. A reasonable hypothesis that could explain this result is that the amount of time the referee has to make a decision affects the final outcome. While referees are not biased when it comes to awarding a free kick, they are when given more time to make a decision, as there are more opportunities for social pressure to work in favour of the home team.

Analysing the impact of ENERGY STAR rebate policies in the US

In this paper, we estimate the impact of rebate policies in various US states on the sales share of ENERGY STAR household appliances. We use annual ENERGY STAR sales data for clothes washers, dishwashers, refrigerators and air conditioners from 2001 to 2006 and the variation in the coverage of rebates across US states and over time to identify the impact of rebate policies. We use, at first, a difference-in-differences approach to estimate this impact. Then, we take into account the possibility of rebate policies being endogenous and use instrumental variables approaches in fixed effects panel data regression models. Results suggest that rebate policies increase the sales share of ENERGY STAR household appliances by 3.3 to 6.6 percentage points, and this represents an impact of 9 to 18 % on the mean level of the sales share of ENERGY STAR household appliances in the US between 2001 and 2006. We conclude that rebates on ENERGY STAR appliances increase the uptake of energy-efficient appliances.

On testing for sphericity with non-normality in a fixed effects panel data model

Building upon the work of Chen et al. (2010), this paper proposes a test for sphericity of the variance–covariance matrix in a fixed effects panel data regression model without the normality assumption on the disturbances.