Lagrange Multiplier Test Research Articles

Unemployment hysteresis in Central and Eastern European countries during EU-membership

AbstractThis study aims to analyse the time series properties of the unemployment rates in 10 Central and Eastern European countries after joining the European Union. Three types of unit root tests were conducted: (1) linear unit root tests, namely ADF, PP, LM, and RALS-LM tests; (2) LM and RALS-LM unit root tests with two structural breaks; and (3) LM and RALS-LM unit root tests with Fourier function. The results reveal that the hysteresis hypothesis is valid for Bulgaria, Czechia, Hungary, Latvia, Lithuania, Romania and Slovenia, whereas the structuralist hypothesis is valid for Estonia and Poland. However, the natural rate hypothesis holds only for Slovakia.

Divergence or convergence: trade globalization, regulatory and environmental quality in QUAD countries – a robust ARDL and decoupling index inquiry

PurposeThe Quadrilateral Group for Security Dialogues (QUAD), comprising Japan, Australia, India, and the USA, has experienced a noteworthy escalation in both environmental depletion and economic performance over the preceding 2 decades. Consequently, it becomes crucial to outline strategies through which the QUAD can attain a harmonious equilibrium between sustainable economic growth and ecological well-being. This research endeavors to dissect the intricate relationships among trade globalization, regulatory quality, and environmental sustainability within the QUAD for the period 1990–2021. The study checks for the Pollution Haven Hypothesis (PHH), and Pollution Halo Effect Hypothesis (PHEH).Design/methodology/approachThe long-run association is based on the autoregressive distributed lag (ARDL) model and bounds test approach to cointegration while divergence or convergence is studied with the help of decoupling index (DI). Results have been verified by applying serial correlation LM test, autoregressive conditional heteroskedasticity (ARCH), and cumulative sum of recursive residuals (CUSUM) tests to ensure the robustness and stability of the model.FindingsThe empirical results of this study affirm the applicability of the PHEH in the contexts of India, Japan, and the USA, whereas the PHH is validated in the case of Australia. Furthermore, the analysis reveals the existence of relative decoupling solely in the case of India. This testifies that the rate of growth of the Indian economy surpasses the rate of growth in ecological footprint (EF), indicating a relative reduction in the intensity of environmental impact per unit of economic growth.Research limitations/implicationsThe empirical findings of our study suggest that countries with effective regulatory systems are better positioned to control and mitigate the potential adverse environmental effects resulting from increased global trade. Thus, policymakers are prompted to reassess the development policies for sustainable economic growth that will minimize adverse environmental repercussions. The implication of the negative relation between urbanization and EF is paramount for policymakers in developing countries seeking strategies for balanced urban development that aligns with environmental sustainability.Originality/valueThe present study is a unique exploration of the impact of trade globalization and regulatory quality on EF, specifically on PHH/PHEH in the context of QUAD.

Perceived Quality and Satisfaction Regarding Private Labels in Romanian Retail

Abstract This article addresses the perception of various customers regarding the private labels of retail companies. Therefore, the scope of this paper is to illustrate and determine whether specific factors such as the opinion, satisfaction and enjoyment of such labels, influence each other and also the perception of the customer, regardless if the customer is aware or not about it. Since these factors also influence the purchasing decision of potential customers, it is interesting to find out the current state of those, and identify any potential for improvement. This paper uses a statistic linear model, that is based on the inference statistic as well as the descriptive statistics. Therefore, tests like the Lagrange multiplier test, known also as the White test, the Durbin Watson test and the Jarque Bera test, were conducted to check the quality and the validity of the model. The results are interesting due to the fact that every time 2 factors were analysed, one test was failed. This does not necessarily mean that the model is unfounded or not valid. This signifies that there might be a better model that suits the behavior of the analysed factors and can possibly predict better their outcome.

THE ROLE OF BUSINESS RISK AS AN INTERVENING VARIABLE ON FACTORS AFFECTING COMPANY VALUE

This study heading to examine the effect of “dividend policy, investment decisions and funding decisions on firm value by applying business risk as an intervening variable. The population is companies in the consumer goods industry sector that are listed on the IDX in 2016-2022. Samples were selected by purposive sampling. Research data were obtained from the official website of the Indonesia Stock Exchange www.idx.co.id and the official website of the company under study. Data analysis was performed using multiple regression methods. The selection of the regression model was carried out through the Chow test, Hausman test, and Lagrange Multiplier test. The classic assumption test includes a multicollinearity test. Hypothesis testing includes the t-test and the coefficient of determination test. To analyze the effect of mediation is done through the Sobel test, Goodman test, and Aroian test. The results of the study show that dividend policy, investment decisions, funding decisions, and business risks affect firm values. The mediation test using the Sobel, Aroian and Goodman method shows that business risk is able to mediate dividend policy on firm value, business risk variables do not mediate funding decisions on firm value. Meanwhile for the mediation test between investment decisions and firm value, different results were obtained between the three test methods carried out, where Sobel and Aroian showed that investment decisions on firm value were not mediated by business risk, while the Goodman Test showed that there is a significant influence of business risk variables as mediating variables.”

Driving Economic Growth through Transportation Infrastructure: An In-Depth Spatial Econometric Analysis

This research investigates the crucial role of transportation infrastructure in influencing economic activity, thus employing advanced econometric methods including Moran’s I index, LM, Hausman, and LR tests to ensure analytical accuracy and select the appropriate spatial model. Our findings reveal that freight volumes across road, waterway, and civil aviation significantly enhance economic activity by bolstering domestic trade, industrial production, and supply chains. Conversely, the impact of passenger turnover is comparatively minor, although it still contributes to labor mobility and urban accessibility. This study highlights the need for strategic investment in transportation infrastructure and efficient public transport systems to foster economic growth and sustainable development. We recommend that policymakers focus on optimizing transportation networks and integrating intelligent transport technologies to boost economic competitiveness and societal well-being. This analysis not only sheds light on the direct economic impacts of transportation but also underscores the broader social implications, thus advocating for a holistic approach to transportation planning and policymaking.

Estimating Missing Panel Data with Regression and Multivariate Imputation by Chained Equations (MICE)

Missing data may occur in various types of research. Regression and multiple imputation by chained equations (MICE) are two methods that can be used to estimate missing data in panel data types. This study aims to compare the accuracy of the missing panel data estimation using the regression and the MICE methods. The data used in this study are 161 random samples of senior high schools and vocational schools in DKI province for the year 2016-2020. Based on the results of the Chow test, Hausman test, and Lagrange Multiplier test on panel data regression, it shows that the appropriate model for the student-teacher ratio (X5) is random, the percentage of teachers who have an educator certificate (X6) is a fixed model with the specific effect of individual school and time, while the percentage of teachers who hold a bachelor degree (X7) is a fixed model with the specific effect of individual. Based on this model, the estimation of missing data is then carried out. The accuracy of the missing data estimation was carried out by comparing the MAPE, MAE, and RMSE values. The results show that the MICE method is quite good for estimating missing data at X5, quite feasible for estimating X6, and very good for estimating missing data at X7. In general, MICE is more accurate than panel data regression

Are cleaner energy and financial technologies needed? Contagion and causality evidence between global fintech markets, energy consumption, and environmental pollution

AbstractFinancial technology (FinTech) depends on high amounts of energy with an upward trend, possibly affecting emissions due to energy consumption (EC). The study investigates tail dependence, contagion, and nonlinear between FinTech, EC, and carbon dioxide emissions (CO2e) with MS-GARCH-copula and MS-GARCH-copula-causality with a daily sample covering 02 Jan 2012–28 December 2022. The method is a generalized version of single-regime GARCH-copula and causality tests to Markov-switching. Empirical results indicated that FinTech, EC, and CO2e series follow nonlinear processes in addition to unit roots as determined by BDS nonlinearity tests and a set of linear and nonlinear unit root tests. Further, for all series, heteroskedasticity and nonlinear forms of heteroskedasticity cannot be rejected by ARCH–LM and White heteroskedasticity tests, leading to the estimation of the series and their joint dynamics by MS-GARCH-copula and a new MS-GARCH-copula based nonlinear Granger-causality test, the RSGCC test, under two distinct regimes characterized with the low and high volatility for extreme tails of data. Positivity and significance of copula parameters under both regimes indicate a high degree of positive but asymmetric tail dependence and contagion between FinTech & EC, in addition to contagion between FinTech & CO2e and EC & CO2e. RSGCC results determine unidirectional causalities from EC to CO2e and from FinTech to CO2e, coupled with bidirectional causality between FinTech and EC, which enhance the dynamics due to feedback effects. The findings of this paper are of importance for two central Sustainable Development Goals. Results could also be used to bring the FinTech markets and EC to the attention of policymakers, researchers, and eco-friendliness-focused portfolio managers. Graphical Abstract

Relationship between sustainable development indicators and SMEs’ development indicators: Evidence from the EU countries

This study aims to identify whether achieving sustainable development goals influences SMEs’ development and assess its degree. The dataset on SMEs’ development indicators and SDGs 2, 8, 9, 12, and 13 for the panel of EU-27 countries in 2011–2020 was collected using Eurostat and OECD datasets. Breusch and Pagan Lagrangian multiplier test for pooled OLS/panel data random effects and Hausman test for fixed/random effects were utilized. The results were in favor of random effect GLS regression for SDG2 models, SDG9 models, and SDG12-13 (Model 1) and fixed effect GLS regression for SDG8 models and SDG12-13 (Model 2), respectively. Based on bibliometric analyses using VOSViewer 14 and a comprehensive literature review, 19 independent variables have been selected from the “Sustainable development indicators” catalog covering five sustainable development goals; SMEs’ turnover and SMEs’ employees employed are used as the dependent variables to reflect SMEs’ development. The empirical evidence suggests a significant relationship between individual sustainable development and SMEs’ development indicators. It was found that all seven sustainable development indicators of SDG 2 (Zero hunger) and SDG 12 (Responsible consumption and production) have a significant relationship with the indicators of SMEs’ development. Instead, only a part (8 out of 13) of the sustainable development indicators of SDG 8 (Decent work and economic growth), SDG 9 (Industry, innovation and infrastructure), and SDG 13 (Climate action) have a significant relationship with two or one of the SMEs’ development indicators. Therefore, achieving sustainability goals stimulates the development of SMEs itself. AcknowledgmentThis study is supported by the British Academy’s Researchers at Risk Fellowships Program (Award Reference: RaR\100673).

Analysis of the Effects of Money Market Fund Mobilization on the Dynamics of Nigerian Economic Growth

Economic growth is a function of some productive efforts among which savings mobilizations is considered very vital. This study examines savings mobilization strategy and its impact on Nigeria’s economic growth during the year 2001-2022.This is vested with the objectives to investigate the effect of banking density, savings rates and money supply on economic growth. The study relies on time series data sourced from the publication of the Central Bank of Nigeria. Gross Domestic Product Growth Rate (GDPGR) was adopted as dependent variable, while Banking Density (BD), Savings Rates (SR) and Money Supply (MS) were the independent variables. Augmented Dickey Fuller (ADF) unit root test was employed, to test the stationarity. The Auto Regressive Distributive Lag (ADRL) was used to ascertain the relationship between the variables alongside Vector Error Correction Model (VCM). Post estimation diagnostic tools used include Breuch-Godfrey serial correlation LM test and the CUSUM test for stability. From the ARDL, β-coefficient and the associated probabilities were adopted to determine the extent and direction of relationship on economic growth. Data were tested at 5% level of significance; it was discovered that banking density and savings rates affected economic growth positively but with insignificant effects, while money supply affected economic growth negatively with insignificant effect. The study therefore recommends amongst others, that stakeholders, be directed towards entrenching higher banking density as opposed to banking desert, and that money supply should be made dynamic in accordance with economic realities.

Investing in Women, Investing in the Planet: Quantifying the Impact of Women's Empowerment on Environmental Sustainability

Objective: This study finds out the correlation between the indicators of women’s empowerment, including variables like gender parity index in tertiary education, female labour force participation and seats held by women in national parliament, and a variable of environmental sustainability such as CO2 emissions (metric tons per capita). The aim is to analyse existing datasets to know the impact of independent variables on dependent variable. Method: The study uses multiple linear regression to evaluate the effects of independent variables indicators of women's empowerment on the dependent variable, CO2 emissions, using secondary data from the World Bank covering the years 1990 to 2022. The Breusch-Pagan and Breusch-Godfrey LM tests are used to look at heteroskedasticity and autocorrelation, respectively, and VIF is used to find multicollinearity. Results and Conclusion: The study concludes that there is a statistically significant relationship between lower CO2 emissions and increases in the percentage of female seats in the national parliament (-3.73) and higher female labour force participation (-6.04). The gender parity index (GPI) in tertiary education, which is -0.2997, does not, however, appear to have a statistically significant impact on CO2 emissions. Implications: This research can serve as a cause for redesigning gender-responsive environmental initiatives and promoting a more sustainable and equitable future. Originality/Value: This study contributes empirical knowledge to the body of literature by showing the potential contribution of women's empowerment in addressing environmental issues and emphasising the significance of taking gender into account in environmental policy and decision-making processes.

Business Leadership in E-Commerce in the USA: The Impact of Blockchain Technology

Due to the evolution of digital finance and the active development of cryptocurrencies, blockchain is no longer just a tool for cryptocurrency extraction or database management but a technology that has a wider range of benefits for every trader who wants to conduct transactions using electronic payment instruments (cost improvement, effective tracking and traceability, verifiable record-keeping, transparency, etc.). The impact of blockchain technology on e-commerce can be viewed through the prism of unprecedented technological capabilities, legal and regulatory issues, customer data analysis, the design of communication channels along the supply chain, and trust and security. The article investigates the effect and the direction of the impact made by changes in digital blockchain technologies on retail prices in US e-commerce during 2014-2023 based on the VECM error correction model (software package – Eviews 12). The stability of the time series of the studied variables was confirmed by the Phillips-Perron test, and the Granger causality test showed the absence of a causal relationship between the studied factors in both directions. Instead, the Johansen Juselius Joint Integration Test showed a long-term balance between the studied variables (this is what allows using the VECM model). The results of the delay test of the studied model by two criteria (AIC and SC) showed that the optimal number of delays for the studied variables is 2. When conducting validity tests of the VECM model (joint integration test, LM test, heterogeneity test, unit root test, etc.), it was found that the model does not suffer from the problem of heterogeneity or self-correlation and meets the stability conditions. The study results indicate a positive impact of changes caused by blockchain technology on e-commerce in the long run (changes in digital blockchain technology explain 44% of retail e-commerce changes), with no short-term effect. Any shock in retail e-commerce will quickly affect changes in digital blockchain technology and vice versa (from the first period).

Function of Non-Performing Loans In The Capital Adequacy Ratio Model of the Banking Sector

Research is being done in order to address the discrepancies in the findings of earlier investigations as well as the phenomenon of non-performing loans (NPL), which cannot account for the effect it has on the CARR. As a result, the researchers used different time series and cross-sectional data in their subsequent studies. Using multiple regression analysis, this type of descriptive quantitative research examines panel data from 22 samples of banking sector firms over a seven-year period. This formula uses the research object, which are companies in the banking sector listed on the Indonesia Stock Exchange, and uses NPL as an intervening variable to maximize the CAR value. Two research models are combined in one model, and each model is subjected to the Chow Test, Hausman Test, Lagrange Multiplier Test, and model selection test stages. Findings in the first model indicate that LDR's negative connection with NPL can be used to explain its impact. These outcomes differ from the relevant theory. Similar to the first study model, where the results are not as relevant as the theory, the results in the second model are also just LDR and may directly explain its effect on CAR with a negative association. It is hoped that these findings would give banking sector managers the best possible direction

The Impact of Fundamental Analysis on Equity Prices: The Food and Drink Sector

This research aims to ascertain the impact of fundamental factors, such as Return on Assets (ROA), Debt Equity Ratio (DER), Price Earnings Ratio (PER), Current Ratio (CR), and Total Assets Turnover (TATO), on stock prices. The study targets on the listed companies in the food and beverage sectors listed on the Indonesia Stock Exchange between 2012 and 2015. The research design is causal research methods, and the sampling technique is purposive sampling method. During the four-year observation period, 11 out of 17 companies met the criteria. The data was analyzed using data regression analysis technique, employing three approaches: Common Effect, two types of effects: random and fixed. Using the F test and t-statistical test, the Hausman test, Chow test model and Lagrange multiplier test were employed for the model selection. By using F tests, the study’s findings showed that ROA, CR, DER, TATO, and PER have an impact on changes in stock prices. The t-statistic test result indicated that while the variables DER, CR, and PER had no effect on the stock price of food and beverage companies, ROA and TATO have a partial influence on the share price.

Modeling Spatial Regimes With Smooth Transitions

In this paper, we introduce a new way of modeling spatial regimes using smooth transitions. We propose an autoregressive spatial lag model where a logistic function captures structural variation in the spatial lag parameter. In the regime-switching spatial lag model with smooth transitions, the effect of the spatial neighbors depends on the transition variable that governs the regime switch. An LM test for detecting nonlinearity is derived, and a simulation study, where the properties of the test are investigated, is conducted. The test shows good power in relatively small samples with moderate deviation from linearity. An empirical application is included, where data on median house prices from the Boston area is used to explore the spatial dependence between census tracts. A smooth shift between regimes governed by the variable property tax rate is found. The smooth spatial lag model performs slightly better than the regular spatial lag model in terms of model fit and capturing spatial dependence.

Threshold Effect of Trade on Climate Change in South Africa

The relationship between trade and climate change is not a simple linear relationship. In this paper, using the threshold regression model, we estimated the effect of trade on climate change in South Africa. The paper applied the LM test to examine the nonlinear inference approach to test whether nonlinearity existed and if the threshold model was relevant to the study. The results show that when energy use is set as the threshold variable, the relationship between trade and climate change measured as methane is U-shaped. Also, in other models of GHG as climate change indicators, the results show that the effect of trade on climate change is not dynamic. This result supports the idea that high and low trade effects may have different impacts on climate change indicators. It is, therefore, recommended that all exporters in South Africa resort to more innovative environmental mechanisms to reduce the contribution to climate. The suggestion for future studies is to consider exports of different sectors to climate change. This approach will avoid the generalization of exporting firms as the worst emitters.

Analysis of the human development index in East Java Province 2017-2021

This research aims to determine Population, Education and Minimum Wages on the Human Development Index. The dependent variable is the Human Development Index, while the independent variables are Population, Education and Minimum Wage. The data used in this research is secondary data which examines data for 5 (five) periods 2017 – 2021 with Regencies/Cities in East Java Province. The research method used is panel data regression analysis. The tool used to carry out testing is Eviews 9. The tests used in this research are the FE, CE, RE, Chow, Hausman and LM tests. The results of this research are: 1) Population is significant and has a positive effect on the Human Development Index in the Regency/City of East Java Province, 2) Education is significant and has a positive effect on the Human Development Index. and 3rd) Minimum Wage has a significant negative effect on the Human Development Index.

Nexus among Exchange Rate Volatility, Inflation, and Economic Growth: A Panel Data Analysis

This study undertakes an examination of the intricate relationships among exchange rate fluctuations, inflation, and economic growth within South Asian nations, namely Pakistan, India, Bangladesh, Sri Lanka, and Nepal. Spanning the temporal horizon from 1990 to 2021, the research endeavors to unveil the repercussions of exchange rate instability on economic growth—a formidable challenge confronted by monetary authorities and policymakers in South Asia. The central focus lies on comprehending the dynamics of exchange rate volatility, inflationary pressures, and their collective impact on economic growth. In the pursuit of these objectives, GDP per capita serves as the yardstick for economic growth, while independent variables encompass a spectrum including broad money supply, exchange rate volatility, inflation, government consumption expenditures, and gross fixed capital formation. The quantification of exchange rate volatility entails the utilization of both the standard deviation and the GARCH (1,1) models. Subsequent to an in-depth analysis, the initial unit test results undergo reevaluation, incorporating the Breusch-Pagan LM, Pesaran CD, and Pesaran scaled LM tests to discern cross-sectional dependence. To address potential data non-stationarity while considering cross-sectional dependence, the Pesaran-CIPS and Pesaran's CADF tests are applied. A pivotal aspect of the research involves the application of a Feasibly Generalized Least Squares (FGLS) regression model. The outcomes of the FGLS panel data regression illuminate a noteworthy finding: exchange rate volatility, quantified through both techniques, significantly and adversely influences economic growth. In contrast, inflation exhibits a statistically insignificant negative impact on economic growth. The study culminates by proffering specific recommendations to policymakers, urging concerted efforts to ensure exchange rate stability and foster sustained economic growth.

ANALYSIS FF FACTORS AFFECTING PROFIT GROWTH OF CELLULAR TELECOMMNUNICATION OPERATOR COMPANIES ON THE INDONESIAN STOCK EXCHANGE

A comparison will be made between the Current Ratio (CR), Net Profit Margin (NPM), and Return on Assets (ROA) in connection to the increase of profits in infrastructure-related cellular telecommunications operator enterprises (XL, Telkomsel, Smartfren, and Indosat) between the years 2016 and 2022. A number of tests are included in the research protocol. These tests are as follows: the Chi-Square test (CoW) for selecting a common effect model, the likelihood ratio test (LM) for selecting a random effect model, the Breusch-Pagan test for detecting heteroscedasticity, the Multicollinearity test for identifying multicollinearity, the regression test with the common effect model (CEM) for determining the effect of independent variables on earnings growth, and the coefficient of determination test for determining the ability of CR, NPM, and ROA to explain earnings growth variability. The data indicates that the activities of mobile telecom operator enterprises operating within the infrastructure sector had a positive influence on the increase of profits derived from CR, NPM, and ROA. In accordance with the results of the LM test, the Common Effect Model is more appropriate than the Random Effect Model. In addition, the Breusch-Pagan test shows the absence of heteroscedasticity in the model. Multicol test also confirmed the absence of multicollinearity problem in the analysis. This study provides important insights into the factors that influence earnings growth in the mobile telecommunications industry in the infrastructure sector. These results can assist company management in designing more effective financial strategies to achieve better earnings growth.

Weak identification with many instruments

Summary Linear instrumental variable regressions are widely used to estimate causal effects. Many instruments arise from the use of ‘technical’ instruments and more recently from the empirical strategy of ‘judge design’. This paper surveys and summarises ideas from recent literature on estimation and statistical inferences with many instruments for a single endogenous regressor. We discuss how to assess the strength of the instruments and how to conduct weak identification robust inference under heteroscedasticity. We establish new results for a jack-knifed version of the Lagrange Multiplier test statistic. Furthermore, we extend the weak identification robust tests to settings with both many exogenous regressors and many instruments. We propose a test that properly partials out many exogenous regressors while preserving the re-centring property of the jack-knife. The proposed tests have correct size and good power properties.

CONVERGENCE OF WHOLESALE ELECTRICITY PRICES ACROSS EUROPEAN MARKETS: ARE WE THERE YET?

European electricity market integration has been a research focus, especially after the third electricity directive emphasizing the internal market. Electricity markets are characterized by immediate consumption with storage and transmission constraints, leading to unique price dynamics. Price convergence in European markets can lead to competitive pricing, advocating market integration. This research examines whether European wholesale spot electricity prices converge. Prior literature uses sigma and beta-convergence to test price convergence. We have examined the stochastic convergence of prices across 19 European nations from 2013 to 2021 utilizing monthly data. For this analysis, we employed LM tests incorporating trend breaks grounded on the RALS regression framework. RALS-LM tests are more powerful than linear tests when structural breaks and nonnormal errors are present. LM and RALS-LM unit root tests with two trend breaks resulted in rejection of the unit root hypothesis for all countries, suggesting relative wholesale prices are stationary. Thus, shocks to relative prices are transient, supporting price convergence at the wholesale level. This result should be considered carefully as it contradicts the results from recent literature that examines retail electricity prices using beta- sigma- and club convergence. The policy implications of this finding can provide a foundation for establishing policies that promote a harmonized and integrated European electricity market.