Artículos de revistas: "Random-effect panel data"

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Huang, Bai, Tae-Hwy Lee y Aman Ullah. "A combined random effect and fixed effect forecast for panel data models". Journal of Management Science and Engineering 4, n.º 1 (marzo de 2019): 28–44. http://dx.doi.org/10.1016/j.jmse.2019.03.004.

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Kencana, Eka N., Darma Arnawa y Ketut Jayanegara. "Memodelkan Impor Beras Menggunakan Regresi Data Panel". Jurnal Matematika 10, n.º 2 (17 de enero de 2021): 135. http://dx.doi.org/10.24843/jmat.2020.v10.i02.p130.

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Abstrak Beras merupakan salah satu komoditas pangan terpenting dunia. Data Fo-od and Agricultural Organizations (FAO) memperkirakan sekitar 90 persen beras duniadihasilkan negara-negara di Benua Asia dengan pusat produksi padi Asia terletak di Ka-wasan ASEAN. Sebagai negara agraris, Indonesia menduduki peringkat ketiga produsenpadi dunia setelah Tiongkok dan India, dan peringkat pertama produsen padi ASEAN.Meski demikian, Indonesia bersama negara-negara produsen lain di ASEAN juga me-lakukan impor beras. Artikel ini bertujuan memodelkan impor beras 5 negara ASEAN.Menggunakan data komoditas beras dari FAO pada periode tahun 2009–2018, 3 jenismodel Regresi Data Panel diaplikasikan untuk memodelkan impor beras. Hasil analisismenunjukkan Random Effect Model (REM) merupakan model terlayak pada impor beras5 negara ASEAN dengan perbedaan jumlah impor pada 2 tahun berturutan, konsumsi,dan produksi beras sebagai variabel-variabel penjelas.Kata kunci: beras, data panel, impor, random effect, regresi.

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Agus Astapa, I. Gede, Gede Suwardika y I. Ketut Putu Suniantara. "ANALISIS DATA PANEL PADA KINERJA REKSADANA SAHAM". Jurnal VARIAN 1, n.º 2 (24 de abril de 2018): 59–69. http://dx.doi.org/10.30812/varian.v1i2.72.

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Mutual funds is another investment opportunity with a more measurable risk as well as return high enough with enough capital is affordable for the community. Mutual fund performance can be measured by several indicators.. Modeling the performance of mutual funds modeled by regression of the data panel. The regression model estimation data panel will do with the three approaches, namely the approach of common effect, fixed effects and random effects. This research purpose to know the performance of mutual funds from stock selection skill variable influences, market timing ability and level of risk with the use of panel data analysis. The results shows that the Fund's performance is affected by the stock selection skill, market timing ability, and the level of risk. Model the right approach to model the performance of mutual funds by using a random effects model.

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Suardin, Misriani, Muhammad Nadjib Bustan y Ansari Saleh Ahmar. "Pemodelan Pertumbuhan Ekonomi Provinsi Sulawesi Selatan dengan Menggunakan Regresi Data Panel". VARIANSI: Journal of Statistics and Its application on Teaching and Research 2, n.º 3 (7 de agosto de 2020): 158. http://dx.doi.org/10.35580/variansiunm14637.

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Abstract. Economic growth is a process for change the economic condition a country or regional by continuously for the better condition as long as definite period. Economic growth in South Sulawesi for 2013-2016 have up and down because many factors have influence it. Like jobless, human capital index, regional revenue, expenditure, and total population. This research was conducted to determine the factors that influence economic growth in South Sulawesi by using data panel regression methods. Panel data regression is a regression by using panel data. Panel data is a statistics analysis method that combines between time series data and cross section data. The result indicates that the result if the regression analysis on the =5% show that the best panel data regression model is random effect model and human capital index variable have significant effect on economic growth with probability value about 0,0227. Meanwhile, jobless, regional revenue, expenditure, and total population no significant.Keywords: Panel Data Regression, Economic Growth, Common Effect Model, Fixed Effcet Model, Random Effect Model

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Irwansyah, Muhammad, R. Ruliana y Muhammad Kasim Aidid. "Analisis Regresi Balanced Panel dengan Komponen Galat Dua Arah pada Kasus Melek Huruf Masyarakat di Provinsi NTB". VARIANSI: Journal of Statistics and Its application on Teaching and Research 3, n.º 1 (8 de marzo de 2021): 10. http://dx.doi.org/10.35580/variansiunm14644.

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Abstract. Analsis regresi adalah suatu metode untuk melihat pengaruh antara satu atau lebih peubah bebas terhadap peubah terikat. Data yang digunakan untuk analisis regresi ada yang berupa penggabungan antara data cross section dengan data time series yang dikenal dengan nama data panel. Data panel yang memiliki jumlah pengamatan waktu yang sama di setiap objek pada tabulasi silang merupakan data panel lengkap (Balanced panel). Penelitian ini mencari nilai dugaan terhadap model regresi data panel dengan komponen galat dua arah yaitu galat pada waktu dan galat pada individu. Analisis regresi data panel dapat menggunakan tiga pendekatan yaitu common effect model, fixed effect model, dan random effect model. Pemilihan model terbaik dari ketiga pendekatan regresi data panel menggunakan uji hausman, uji chow, dan uji lagrange multipler. Dalam penelitian ini didapatkan model terbaik yaitu model random effect dimana peubah yang memiliki pengaruh signifikan terhadap melek huruf di Provinsi NTB yaitu rasio murid guru tingkat SMP rasio murid guru tingkat SMA, dan persentase penduduk miskin. Model regresi data panel yang terbentuk yaitu: Y = 117,5728 - 0,1967X5 - 0,3091X6 - 0,3297X7 + eKeywords: regresi data panel, common effect model, fixed effect model, random effect model, melek huruf.

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Xu, Lei y Jun Shao. "Estimation in Longitudinal or Panel Data Models with Random-Effect-Based Missing Responses". Biometrics 65, n.º 4 (7 de mayo de 2009): 1175–83. http://dx.doi.org/10.1111/j.1541-0420.2009.01195.x.

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Drukker, David M. "A Generalized Regression-adjustment Estimator for Average Treatment Effects from Panel Data". Stata Journal: Promoting communications on statistics and Stata 16, n.º 4 (diciembre de 2016): 826–36. http://dx.doi.org/10.1177/1536867x1601600402.

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I illustrate that the simple regression-adjustment estimator is inconsistent for the average treatment effect when the random effects affecting treatment assignment are correlated with the random effects that affect the potential outcomes. I present a simple parametric estimator that is consistent in this case.

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Olajide, Johnson Taiwo, Jubril Oluwatoyin Fantola y Olufemi Aderemi Ayansola. "Measuring economic growth in OPEC countries : A panel data approach". International Journal of Applied Mathematical Research 4, n.º 2 (30 de abril de 2015): 345. http://dx.doi.org/10.14419/ijamr.v4i2.4544.

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Most of the developing and under-developed countries have been facing a lot of challenges on the issue of economic growth, despite the fact that they are endowed with both natural and human resources. This study examines the determinants of real per Capita GDP growth in Organization of the Petroleum Exporting Countries (OPEC) using a panel of twelve countries for the period of 1986 and 2010.The pooled Ordinary Least Squares (OLS), Fixed Effect (FE) and Random Effect (RE) models were employed to assess the relationship between CGDP and other economic variables used. The result showed that price level of consumptions (pc) and investment share (ci) are the important factors of CGDP that contribute to the economic growth of OPEC countries. The result also established that exchange rate (Xrat), price of GDP (p), purchasing power parity (ppp) and ci have a positive influence on CGDP. The test statistic revealed that Random Effects Model (REM) estimator is more efficient than OLS and that there is no significance difference between Fixed Effects Model (FEM) and REM estimators.

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Olajide, Johnson T. y Olusanya E. Olubusoye. "Estimating Dynamic Panel Data Models with Random Individual Effect: Instrumental Variable and GMM Approach". Journal of Statistics Applications & Probability 5, n.º 1 (1 de marzo de 2016): 79–87. http://dx.doi.org/10.18576/jsap/050107.

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Marquart, Louise y Michele Haynes. "Misspecification of multimodal random‐effect distributions in logistic mixed models for panel survey data". Journal of the Royal Statistical Society: Series A (Statistics in Society) 182, n.º 1 (21 de junio de 2018): 305–21. http://dx.doi.org/10.1111/rssa.12385.

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Lumadya, Adi. "UKURAN PASAR UKURAN PASAR (Market Size) DAN INVESTASI ASING LANGSUNG DI ASEAN". JAE (JURNAL AKUNTANSI DAN EKONOMI) 1, n.º 1 (1 de septiembre de 2016): 26. http://dx.doi.org/10.29407/jae.v1i1.430.

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The main objective of this study was to examine the influence of some economic variables that include market size proxied with income per capita, economic growth, and exports to the Foreign Direct Investment in the member countries of ASEAN-9. The analytical tool used is the Least Squares Regression (Ordinary Least Square) and Panel Data. In the Data Panel will look for similarities in effect is Fixed (Fixed Effect) and the effect is Random (Random Effect). The results of the analysis are: Based on the analysis of OLS concluded that the variable size of the market (market size) were proxied with Per Capita Income (GDPP), Economic Growth (EG), and exports (EG) significantly affects the Direct Foreign Investment. Based on the analysis of Panel Data with Fixed Effect Method concluded that the variable size of the market (market size) were represented with per capita income (GDP), Economic Growth (EG), and exports (EG) significantly affects the Direct Foreign Investment. Based on the analysis of Panel Data with Random Effect method concluded that the variable size of the market (market size) were proxied with per capita income (GDP), Economic Growth (EG), and exports (EG) significantly affects the Direct Foreign Investment. Keywords: Foreign Direct Investment, Fixed Effect, Random Effect

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Aguguom, Theophilus Anaekenwa. "Operational Risks and Equity Returns: Dynamic and Static Panel Data Analyses". Asian Journal of Finance & Accounting 12, n.º 2 (13 de octubre de 2020): 58. http://dx.doi.org/10.5296/ajfa.v12i2.17362.

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This study investigated the effect of operational risk on equity returns of Deposit Money Banks (DMBs), using a population consisted of 19 listed deposit money banks in the Nigeria Stock Exchange. 15 DMBs were purposively selected for a period of 15 years 2005 to 2019. Descriptive and inferential statistics were explored for the data analysis which was sourced from the published financial statements of the banks, using dynamic and static panel data. Diagnostics tests were carried out since the application of the Hausman test provided the criteria for choosing between Random Effect Models and Fixed Effect Models. Breusch and Pagan Lagrangian multiplier test was employed to confirm the Hausman test results in order to decide between Random Effects and Pooled OLS. Correlation Matrix for multicollinearity test and cross-sectional dependent test were equally carried out for the study. Three models were estimated, based on the three proxies of the dependent variable. The study found that operational risk had a statistically positive significant effect on return on equity (ROE), while operational risk equally exhibited statistically positive significant effect on ROA. When the controlling variable of FSIZE was introduced, the study exhibited stronger effects which demonstrates that operational risk had a statistically positive effect on ROE, while operational risk with FSIZE had a statistically positive effect on ROA. The study recommends that DMBs managers should carefully carry out due diligence on loan applicants, to ascertain performance trend and creditworthiness of potential and prospective borrowers before advancing loans in order to reduce huge profiles of credit risk exposures.

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Wooldridge, Jeffrey M. "Fixed-Effects and Related Estimators for Correlated Random-Coefficient and Treatment-Effect Panel Data Models". Review of Economics and Statistics 87, n.º 2 (mayo de 2005): 385–90. http://dx.doi.org/10.1162/0034653053970320.

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Elewa, May M. y Rasha El-Haddad. "The Effect of Audit Quality on Firm Performance: A Panel Data Approach". International Journal of Accounting and Financial Reporting 9, n.º 1 (3 de enero de 2019): 229. http://dx.doi.org/10.5296/ijafr.v9i1.14163.

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This study attempts to examine the effect of audit quality on firm performance. It uses financial statements of non-financial firms listed as EGX 100. The population studied consists of thirty non-financial firms. The study covers a five year period 2010-2014. It applies panel data analysis. Independent Variables are Auditor Experience (measured by Big-4) and Auditor Independence (measured by auditor Rotation ROT). Dependent Variables are Return on Assets ROA and Return on Equity ROE. In accordance with the Random Effect Model results, BIG 4 and ROT have an insignificant impact on the ROA and ROE of the firm. External and internal financial statement users may benefit from the study only when dealing with high-profit firms.

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Halistin, Halistin, Vita Ratnasari, Santi Puteri Rahayu y Tandri Patih. "ESTIMASI PARAMETER MODEL PROBIT PADA DATA PANEL MENGGUNAKAN OPTIMASI BFGS". BAREKENG: Jurnal Ilmu Matematika dan Terapan 14, n.º 2 (7 de septiembre de 2020): 167–80. http://dx.doi.org/10.30598/barekengvol14iss2pp167-180.

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Salah satu model yang dapat menjelaskan pola hubungan antara variabel dependen yang bersifat kategorik dengan variabel independen adalah regresi probit. Dalam regresi probit, variabel independen dapat bersifat kategorik atau kontinu. Regresi probit mrnggunakan fungsi link dari distribusi normal standar. Jika pemodelan regresi probit melibatkan data silang dan deret waktu, disebut model probit data panel. Estimasi parameter model probit data panel random effect menggunakan maximum likelihood estimation (MLE) dengan pendekatan Gauss Hermite Quadrature. Proses iterasi menggunakan metode BFGS. Metode ini digunakan untuk mendapatkan hasil estimasi parameter yang closed form.

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Rahim, Manat, Armin Armin, La Ode Suriadi y Muh Armawaddin. "INFRASTRUCTURES’ EFFECT ON ECONOMIC GROWTH IN SOUTHEAST SULAWESI". TRIKONOMIKA 18, n.º 1 (29 de junio de 2019): 8. http://dx.doi.org/10.23969/trikonomika.v18i1.1134.

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The aim of the research is to analyze the effect of infrastructures on economic growth in Southeast Sulawesi. The data used the secunder data which formed time series-based. The data was obtained by publication and legal documents of Statistic Center Unit and relevant institution. The method of analysis used ordinary least squares with panel data. Thus, the data analysis of this research was regretion model with panel data. To estimate regretion of panel data, the researcher used common effect,fixed effect and random effect method. The findings of this research showed that insfrastructures comprised road, harbor, water and electicity simultaniously and significantly influenced the economic growth in Southeast Sulawesi. Partially, only harbor and electricity significantly affected on the economic growth Southeast Sulawesi.

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Muhammad, Sani, Suleiman Shamsuddeen y Ismail G. Baoku. "ROBUST PARAMETER ESTIMATION FOR RANDOM EFFECT PANEL DATA MODEL IN THE PRESENCE OF HETEROSCEDASTICITY AND INFLUENTIAL OBSERVATIONS". FUDMA JOURNAL OF SCIENCES 4, n.º 4 (13 de agosto de 2021): 561–69. http://dx.doi.org/10.33003/fjs-2020-0404-689.

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Panel data estimators can strongly be biased and inconsistent in the presence of heteroscedasticity and anomalous observations called influential observations (IOs) in Random effect (RE) panel data model. The existing methods (LWS, WLSF, WLSDRGP) address only the problem of IO but fail to remedy the combine problem of heteroscedasticity and IOs. Therefore, in this research we develop a method that will remedy the combine problem of heteroscedasticity and IOs based on robust heteroscedasticity consistent covariance matrix (RHCCM) estimator and fast improvised influential distance (FIID) weighting method denoted by WLSFIID. The simulation and numerical evidences show that our proposed estimation method is more efficient than the existing methods by providing smallest bias, and smallest standard error of HC4 and HC5.

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Shrestha, Purna Man. "Effect of Dividend on Stock Market Price: A Panel Data Approach". Management Dynamics 23, n.º 1 (9 de marzo de 2020): 199–208. http://dx.doi.org/10.3126/md.v23i1.35579.

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Dividend policy is major concern for investor, managers and policy makers. Proper dividend policy helps to achieve the wealth maximization goal of the firm. This study has examined the impact of dividend on stock market price of Nepalese enterprises. For this purpose 33 dividend paying companies listed on NEPSE has been selected as sample. Likewise, this study used unbalance panel data for the period of 2000/01 to 2018/19. Breusch and Pagan Lagrangian multiplier test concluded that Pooled regression model is not appropriate and Hausman test concluded that Random Effect model is not appropriate for the data used in this study. Thus, this study adopted Fixed Effect model to analyze the impact of dividend on stock market price. This study concluded that there is significant impact of dividend on stock market price of Nepalese enterprises after controlling return on equity, earnings per share and return on equity. Finally, this study concluded that cash dividend has significant negative and stock dividend has significant positive impact on stock market price of Nepalese enterprises.

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Singh, Narinder Pal y Mahima Bagga. "The Effect of Capital Structure on Profitability: An Empirical Panel Data Study". Jindal Journal of Business Research 8, n.º 1 (6 de marzo de 2019): 65–77. http://dx.doi.org/10.1177/2278682118823312.

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One of the most perplexing issues faced by finance managers is to know about the effect of capital structure on the profitability of firm. Many studies have been carried out to examine the effect of capital structure on the profitability of firms, but most of them belong to other parts of the world, and only few studies have been conducted in India. Thus, the present study has been undertaken to evaluate the effect of capital structure on the profitability of Nifty 50 companies listed on National Stock Exchange of India from 2008 – 2017. The data has been analyzed by using descriptive statistics, correlation and multiple panel data regression models. Four different regression models have been used to study the relationship between capital structure and profitability. In these models, we study the individual effect of total debt and total equity ratios on profitability, that is, ROA and ROE. All four models have been tested with pooled OLS, fixed effects, and random effects. We conclude that there is significant positive impact of capital structure on firm’s profitability.

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ASTUTI, NI MADE ARY DHARMA WIDYA, MADE SUSILAWATI y NI LUH PUTU SUCIPTAWATI. "IMPLEMENTASI DATA PANEL SPASIAL TERHADAP TINGKAT PRODUK DOMESTIK REGIONAL BRUTO DI PROVINSI BALI". E-Jurnal Matematika 10, n.º 2 (24 de mayo de 2021): 46. http://dx.doi.org/10.24843/mtk.2021.v10.i02.p319.

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Gross Regional Domestic Product (GRDP) is an economic indicator to see the economic movements of a region during a certain period, whether based on current and constant price. Economic activities in a region use the GRDP calculation based on current prices by industrial base year 2010. In 2019, Bali's economic growth increased by , exceeding national economic growth of . Using spatial panel data in analysis consists of common effect model, fixed individual effect model, fixed time effect model, random effect model, and spatial lag fixed effect model. The best model to modeling GRDP Bali Province is spatial lag fixed effect which has a difference in constant values ??at any time, with of 99.41 percent, the remaining is explained by other variables not examined

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Iordache, Mihaela y Mihaela Matei. "Explaining Recent Romanian Migration: A Modified Gravity Model with Panel Data". Journal of Social and Economic Statistics 9, n.º 1 (1 de agosto de 2020): 46–64. http://dx.doi.org/10.2478/jses-2020-0006.

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AbstractThe present paper contributes to studies on Romanian emigration from a demographic, spatial, and temporal perspective. The purpose of this paper is to assess the selected economic and demographic variables’ impact on the volume of Romanian emigration to the European Union (EU) during 2010-2017. The analysis was done using a gravity model. The models used in this study are the fixed effect model (FEM) and the random effect model (REM), both applied to panel data. The results show that the economic and demographic factors have a significant influence on the emigration’s destination, and the socio-economic and demographic situation in the host country determines the flow migration from Romania. The paper strengthens the literature through an empirical analysis of the economic and demographic determinants of Romanian emigration to the EU from the perspective of the country of origin.

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Kahfi, Ahmad Sohibil. "DETERMINANTS OF INDONESIA’S EXPORTS OF MANUFACTURED PRODUCTS: A PANEL DATA ANALYSIS". Buletin Ilmiah Litbang Perdagangan 10, n.º 2 (31 de diciembre de 2016): 187–202. http://dx.doi.org/10.30908/bilp.v10i2.54.

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Nilai ekspor Indonesia terus mengalami penurunan sejak 2012. Masalah ini menarik perhatian pemerintah Indonesia untuk segera meningkatkan performa ekspor, dimana salah satu sektor yang dapat ditingkatkan adalah sektor manufaktur. Studi ini menganalisis faktor penentu ekspor manufaktur di Indonesia sejak 2005 sampai 2014. Faktor utama yang dianalisis antara lain adalah nilai tukar rupiah, foreign direct investment (FDI), gross domestic product (GDP), dan kebijakan perdagangan. Faktor tersebut dianalisis menggunakan regresi data panel dengan pendekatan random effect model. Hasil dari analisis menunjukkan bahwa perubahan relatif dari nilai tukar, real GDP, jarak dua negara, dan tarif secara signifikan memengaruhi ekspor manufaktur di Indonesia. Beberapa rekomendasi terkait untuk pemerintah Indonesia antara lain adalah dengan menjaga ekspor Indonesia ke negara-negara yang memiliki GDP tinggi, memperluas pasar ekspor Indonesia, menjaga stabilitas nilai tukar rupiah, mendukung industri lokal menggunakan teknologi maju, dan mendukung penyederhanaan proses impor. Indonesia’s export has been decreasing since 2012. This problem has raised government’s attention to increase the export performance. One sector that can be improved is manufacturing. This study analyzes the determinants of Indonesia’s manufacturing export from 2005 to 2014. The major factors examined in this study include real exchange rate, foreign direct investment (FDI), gross domestic product (GDP) and trade policies. Those factors are examined by using panel data regression with a random effect model. The results revealed that relative change of exchange rate, real GDP, distance between two countries and average tariffs significantly affected the Indonesia’s manufacturing export. It is recommended that Indonesian government maintains the exports to countries which have high GDP, expand the export market, stabilize Rupiahs exchange rate, encourage local industries to use advanced technologies, and facilitate the simplification of import procedures.

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Rouksar-Dussoyea, Bibi, Ho Ming-Kang, Raja Rajeswari y Benjamin Chan Yin-Fah. "Economic Crisis in Europe: Panel Analysis of Inflation, Unemployment and Gross Domestic Product Growth Rates". International Journal of Economics and Finance 9, n.º 10 (10 de septiembre de 2017): 145. http://dx.doi.org/10.5539/ijef.v9n10p145.

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This panel analysis study is conducted to examine the relationship between inflation rates (CPI) and unemployment rates (HUR) with the Gross Domestic Product growth rates (GDP), before and after the 2008 European crisis. Quarterly data for 18 consecutive years and six sample countries from Europe (Austria, France, Germany, Greece, Hungary and United Kingdom) have been considered in the panel. In order to get a more profound understanding of the impacts of the European crisis on the relationship between the variables, the panel data set has been classified into 3 separate panels, such that Panel 1 (1999Q1-2007Q4) represents before-crisis panel, Panel 2 (2008Q1-2016Q4) represents the during/after crisis panel and lastly, Panel 3 (1999Q1-2016Q4) represents the long-run panel. Panel 1 is subject to the Fixed Effects with LSDV model, whereby four out of the six countries are significant, and CPI and HUR are insignificant predictors of the GDP. Both Panel 2 and Panel 3 are subject to the Two-way Random Effects model, whereby both CPI and HUR have negative significant effect on GDP. Granger Causality test has also been carried out to determine whether causality is present among variables, based on each panel.

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Lucky, Lucky Anyike y Agilebu Ogechi Michael. "Leverage and Corporate Financial Distress in Nigeria: A Panel Data Analysis". Asian Finance & Banking Review 3, n.º 2 (10 de agosto de 2019): 26–38. http://dx.doi.org/10.46281/asfbr.v3i2.370.

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This study examined the effect leverage on corporate financial distress of quoted manufacturing firms in Nigeria. The objective is to examine if financial leverage have any effect on financial distress of the Nigeria firms. Cross sectional data was sourced from financial statement of ten quoted manufacturing firms. Z-Score and Changes in operating profits was proxy for corporate financial distress while debt equity ratio, short, long term debt and total debt to total assets were proxy for leverage. After cross examination of the validity of the pooled effect, fixed effect and the random effect, the study accepts the fixed effect model. Findings reveal that financial leverage have positive effect on financial distress measured by the z-score while total debt ratio and debt equity ratio have positive effect on financial distress measured by changes on operating profits while short term debt and long term debt have negative effect on operating profits. From the regression summary, the study concludes that leverage have significant effect on corporate financial distress. We recommend that Financial structure of the manufacturing firms ought to be adequately planned to safeguard the interest of the equity holders, shareholders and financial requirements of the firm and the firms should formulate policies of increasing its equity capital as oppose to debt and that Implementable investment policies should be formulated and the business environment should be well examined. Recognizing faults of investment might be paramount to develop the business’s financial performance, since it specifies the loopholes which corrective decision can be applied.

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Kevin, Kevin, Aning Kesuma Putri y Aja Nasrun. "Pengaruh inflasi dan laju pertumbuhan penduduk terhadap kemiskinan di Sumatera Bagian Selatan tahun 2011-2018". SOROT 15, n.º 1 (28 de abril de 2020): 33. http://dx.doi.org/10.31258/sorot.15.1.33-42.

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Penelitian ini bertujuan untuk mengetahui pengaruh inflasi dan laju pertumbuhan penduduk terhadap kemiskinan di Sumatera bagian Selatan (Sumbagsel) tahun 2011-2018. Penelitian ini menggunakan pendekatan kuantitatif. Data yang digunakan adalah data panel ibu kota provinsi di Sumbagsel yang terdiri dari Palembang, Pangkalpinang, Bandar Lampung, Bengkulu, dan Jambi tahun 2011-2018. Teknik analisis data dalam penelitian ini menggunakan analisis regresi data panel dengan model Random Effect. Hasil penelitian menunjukkan bahwa secara simultan variabel inflasi dan laju pertumbuhan penduduk berpengaruh signifikan terhadap kemiskinan. Secara parsial variabel inflasi tidak berpengaruh signifikan terhadap kemiskinan sedangkan variabel laju pertumbuhan penduduk berpengaruh signifikan terhadap kemiskinan.This research aimed to find out the effect of inflation and population growth rate on the poverty in Southern Sumatera in 2011-2018. This research used the quantitative approach. The data used is panel data of the capital of province in Southern Sumatera which consists of Palembang, Pangkalpinang, Bandar Lampung, Bengkulu, dan Jambi in 2011-2018. The data analysis technique was the panel data regression analysis using random effect model. The result of the research showed that simultaneously the variable of inflation and population growth rate have a significant effect on the poverty. Partially the variable of inflation have no significant effect on the poverty while the variable of population growth rate has a significant effect on the poverty.

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Kengatharan, Lingesiya. "Determinants of Dividend Policy in Sri Lanka: The Panel Data Analysis". Asia-Pacific Management Accounting Journal 16, n.º 2 (31 de agosto de 2021): 289–313. http://dx.doi.org/10.24191/apmaj.v16i2-11.

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The study aimed to emphasize the determinants of dividend policy in Sri Lankan firms. This study was conducted with 80 non - financial companies which were listed on Colombo Stock Exchange (CSE). The empirical research was focused on panel data analysis, and data was collected from annual reports for a five year period from 2013 to 2017. This study explored selected factors that influence dividend policy, including sales growth, leverage, firm size, profitability, EPS, liquidity, and risk. The panel data analysis employed pooled OLS, fixed - effect, and random - effect models. Based on the analysis, the fixed - effect model was thought to be the best fit for studying the factors that affect dividend policy. According to the outcome of fixed-effect model, among the seven input variables considered in this study, profitability, EPS, and risk were negatively linked to dividend policy. However, no significant relationship was found between dividend policy and sales growth, leverage, firm size, or liquidity. The findings contribute to the understanding that three parameters namely: profitability, EPS, and risk have been recognized as factors affecting dividend payouts in CSE’s listed companies. Hence, policymakers will be able to concentrate on the factors that influence shareholder wealth maximization. Keywords: profitability, EPS, risk, dividend payout

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Singla, Harish Kumar y Pradeepta Kumar Samanta. "Determinants of dividend payout of construction companies: a panel data analysis". Journal of Financial Management of Property and Construction 24, n.º 1 (1 de abril de 2019): 19–38. http://dx.doi.org/10.1108/jfmpc-06-2018-0030.

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Purpose This paper aims to examine the determinants of the dividend policy of the construction companies in India. Design/methodology/approach Data from 2011 to 2016 (six years) of 45 listed construction companies in India are collected, and a strong balanced panel is created. Dividend per share is dependent variable, and profitability, unstable earnings, institutional holding, cash flow, tangibility, liquidity, growth opportunities, age of the firm, life cycle, leverage, size of firm and taxation are explanatory variables. The panel is tested for stationarity and finally fixed and random-effect panel regression model with robust estimation option is performed. Findings The random effect model is found fit with an R2 of 62 per cent, and profitability, life cycle and size of the firm show a significant positive effect on dividend payment. Cash flow shows a negative significant relationship, indicating the presence of agency problem. Rest of the variables indicated an insignificant relationship. Research limitations/implications The study is carried out on a small sample of 45 companies with data of only six years. Further, there may be behavioral and psychological factors that drive the decision to declare dividend. Those factors have not been considered in present study. Despite considerable efforts, the author could not find more studies specific to the construction sector. Hence, the variables identified in the present study are more generic, even though a few sector-specific studies have been included. Originality/value The dividend policy determinants for the construction sector in India are investigated, and a comprehensive model based on 12 explanatory variables is tested to find the drivers of dividend payout in Indian construction companies. From the investor’s point of view, the sector has immense potential in terms of dividend as well as capital appreciation. Therefore, the study can be useful to the investors to understand the drivers of dividend payout in the construction sector. It can also be crucial for companies to create an appropriate dividend policy so as to attract and retain investors. The study contributes significantly to the existing body of knowledge by recommending the salient drivers of dividend payout in the construction sector based on a comprehensive dataset and using robust methodology.

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Pratiwi, Hasih, Ardina Nilam Prawastyorini y Sugiyanto Sugiyanto. "Analisis Data Panel pada Tingkat Pengangguran Terbuka Kabupaten/Kota di Pulau Jawa". Jurnal Matematika, Statistika dan Komputasi 16, n.º 1 (27 de junio de 2019): 51. http://dx.doi.org/10.20956/jmsk.v16i1.6713.

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Unemployment rate is the percentage of the number of unemployed to the total labor force, it has become some problems in economic development. The aim of this study is to choose the best model between common, fixed, and random effects in modeling open unemployment rate of regency/city in Java. It based on open unemployment rate with several influence factors in Java Island 2010-2016 which are panel data types. The best model choosen based on the results of the Chow test and Hausman test. The fixed effect model was obtained as the best model with a value of 79,26 percent.

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Arum, Prizka rismawati. "Analisis Faktor-Faktor yang Mempengaruhi Jumlah Penduduk di Kota Semarang Menggunakan Metode Regresi Data Panel". J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika 12, n.º 2 (31 de diciembre de 2019): 36–41. http://dx.doi.org/10.36456/jstat.vol12.no2.a2227.

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Residents are all people who live in the geographical area of Indonesia for six months or more and or those who have been domiciled for less than six months but aim to settle. Population growth is caused by two components, namely: fertility and mortality. To find out how big the relationship between the population and the number of births and deaths in each sub-district of Semarang, must observed in several specific time periods and places at once. So in this study, the panel data regression method was used. In panel data regression testing, the results show that the panel data regression model formed to determine the factors that influence the level of population is the random effect model. In this model all assumptions are fulfilled. Significant factors affecting population are number of births. Births and deaths affect the population of 99.95% and the remaining 0.05% is influenced by other factors not examined Penduduk adalah semua orang yang berdomisili di wilayah geografis Indonesia selama enam bulan atau lebih dan atau mereka yang berdomisili kurang dari enam bulan tetapi bertujuan menetap. Pertumbuhan penduduk diakibatkan oleh dua komponen yaitu: fertilitas dan mortalitas. Untuk mengetahui seberapa besar keterkaitan antara jumlah penduduk dengan jumlah kelahiran dan kematian di setiap kecamataan Kota Semarang, harus diamati dalam beberapa periode waktu tertentu dan beberapa tempat secara bersamaan. Sehingga dalam penelitian ini digunakan metode regresi data panel. Dalam pengujian regresi data panel, didapatkan hasil bahwa Model regresi data panel yang terbentuk untuk mengetahui faktor-faktor yang mempengaruhi tingkat jumlah penduduk adalah model random Effect. Pada model tersebut semua asumsi terpenuhi. Faktor yang signifikan mempengaruhi jumlah penduduk adalah jumlah kelahiran. Kelahiran dan kematian mempengaruhi jumlah penduduk sebesar 99.95% dan sisanya sebesar 0.05% dipengaruhi oleh faktor- faktor lain yang tidak di teliti.

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Suliyanto. "Environmental quality index modeling in Indonesia using ordinal probit regression approach for panel data with random effect". Journal of Physics: Conference Series 1277 (julio de 2019): 012044. http://dx.doi.org/10.1088/1742-6596/1277/1/012044.

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Sakti, Muhammad Rizky Prima y Abdul Qoyum. "Testing The Warrants Mispricing and Their Determinants: The Panel Data Models". Global Review of Islamic Economics and Business 5, n.º 2 (7 de diciembre de 2017): 118. http://dx.doi.org/10.14421/grieb.2017.052-05.

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This paper empirically studied the impact of several variables such as moneyness, stock return, maturity, and volatility on the warrant mispricing. We selected 4 companies listed in Bursa Malaysia such as MHC Plantations Bhd, MKH Bhd, YFG Bhd, and UNISEM to investigate the mispricing of warrants. Subsequently, panel time series data employed with daily basis from 30 June 2010 until 30 June 2013. The Black-Scholes Option Pricing Model (BSOPM) used to determine the mispricing of warrant. Several panel data techniques employed in this study such as pooled-OLS, fixed effect model (FEM), and random effect model (REM). In turn, we found that FEM is well explained the determinants of warrant mispricing. Thus, empirical results suggest that moneyness, maturity, and volatility are positively and significantly explained the mispricing of warrant, while stock return does not give an impact toward the warrant mispricing. The BSOPM is consistently mispricing the warrant either in-the-money (ITM) or out-the money (OTM) warrants. The market is not efficient on the warrants traded for four companies observed

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Alalawneh, Mustafa Mohammad y Azizun Nessa. "The Impact of Foreign Direct Investment on Unemployment: Panel Data Approach". Emerging Science Journal 4, n.º 4 (1 de agosto de 2020): 228–42. http://dx.doi.org/10.28991/esj-2020-01226.

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The purpose of this study was to investigate the impact of foreign direct investment on unemployment in six countries in the Middle East and North Africa, Egypt, Jordan, Lebanon, Morocco, Tunisia, and Turkey, as this region is considered one of the most regions in the world with a high rate of unemployment. The study employed panel data for the period from 1990 to 2018, where three economic models were used to examine the impact of FDI on unemployment, male unemployment, and female unemployment, in the long run, using the Fixed Effect Model (FEM) and Random Effect Model (REM), in addition to finding the causal relationship in the short term using Panel VAR (Granger causality tests). The results showed that FDI reduces the unemployment rate, the male unemployment rate, and the female unemployment rate in the long run. The results of the study also revealed that there is no causal relationship in the short term between FDI and unemployment in its various forms, while there is a bidirectional causal relationship between FDI and exports according to the three economic models. This paper is the first of its kind in terms of examining the effect of FDI on unemployment in the six countries as a grouped and a sample of the MENA region.

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Mustika, Fiky Nila, Eni Setyowati y Azhar Alam. "Analysis Of Effect Of ZIS (Zakat, Infaq, And Shadaqah), Regional Domestic Products Of Bruto, Regional Minimum Wage And Inflation On Levels Poverty In Indonesia 2012 – 2016". Journal of Islamic Economic Laws 2, n.º 2 (1 de julio de 2019): 193–211. http://dx.doi.org/10.23917/jisel.v2i2.8679.

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This study investigated the impact of ZIS (Zakat, Infaq, and Sadaqah) Gross Regional Domestic Products, Regional Minimum Wages, and Inflation on Poverty Levels in Indonesia during the 2012-2016 period. .This paper used secondary data in the panel data form. This research conducted a quantitative approach using panel data regression. Based on the results of the panel data testing, the best model chosen is the Random Effect Model (REM). Variables of gross regional domestic products and regional minimum wages have a significant effect on poverty levels in Indonesia while the variables of zakat, infaq, and shadaqah (ZIS) and inflation do not influence the level of poverty in Indonesia.

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Towhid, ASM, Shinta Amalina Hazrati Havidz y Mohammed Ameen Qasem Ahmed Alnawah. "BANK-SPECIFIC AND MACROECONOMIC DETERMINANTS OF NON-PERFORMING LOANS OF COMMERCIAL BANKS IN BANGLADESH". Dinasti International Journal of Management Science 1, n.º 1 (27 de octubre de 2019): 86–101. http://dx.doi.org/10.31933/dijms.v1i1.28.

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The prime objective of this research is to identify the main determinants of non-performing loans in the commercial banking system of Bangladesh for the period 2011-2016 using panel data modeling. This paper uses balanced panel data method to examine both bank-specific (return on average assets, net loans to deposit ratio, bank size, cost-to-income ratio, and capital adequacy ratio) and macroeconomic (real GDP growth rate and inflation rate) variables. To attain the objectives, the present research analyzed historical data and panel data model using secondary data. To examine panel data modeling, the researcher considers 16 private commercial banks in Bangladesh and executed pooled OLS model, fixed effect model, random effect model and random effect with the robust standard error. The researcher found a negative significant relationship for return on average assets, net loans to deposit ratio and inflation rate in relation to NPLs and results are supporting the previous researcher. Based on the findings, the study offers some valuable strategies to the management to improve return on average assets, net loans to deposit ratio and inflation rate to reduce the NPLs at least under the tolerance level. The study also delineates the limitations of this work and direction for future research.

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Shrestha, Purna Man. "Determinants of Financial Performance of Nepalese Commercial Banks: Evidence from Panel Data Approach". NRB Economic Review 32, n.º 2 (1 de octubre de 2020): 45–59. http://dx.doi.org/10.3126/nrber.v32i2.35300.

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The impact of bank specific factors on the financial performance of Nepalese commercial banks is analyzed in this paper. The financial performance is measured by using return on assets (ROA). Similarly, managerial efficiency (ME), liquidity (LIQ), credit risk (CR), assets quality (AQ) and operational efficiency (OE) is used as proxy of bank specific factors. This study used panel data of 17 commercial banks for the period of 2010/11 to 2017/18. Breusch and Pagan Lagrangian multiplier test showed that Pooled Regression model is not appropriate and Hausman test concluded that Fixed Effect model is appropriate rather than Random Effect model. Using the Fixed Effect model; this study concludes that bank specific factors have significant impact on financial performance of Nepalese commercial banks. Finally, this study reveals that ME, AQ and OE have significant positive impact, and CR has negative impact on the financial performance of Nepalese commercial banks.

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Sihaloho, Estro Dariatno. "PENGARUH BELANJA KESEHATAN TERHADAP ANGKA HARAPAN HIDUP KABUPATEN KOTA DI JAWA BARAT". Ekspansi: Jurnal Ekonomi, Keuangan, Perbankan dan Akuntansi 11, n.º 1 (31 de mayo de 2019): 117. http://dx.doi.org/10.35313/ekspansi.v11i1.1308.

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This paper has two objectives. The first is to estimate the effect of health expenditure on life expectancy in regencies and cities in West Java Provinces. The second is to estimate the effect of the number of poor people on life expectancy in regencies and cities in West Java Provinces. Life expectancy is a measurement of the average time of human lives. This paper uses three-technique of Data Panel regression model: Pooled OLS, Fixed Effect Model and Random Effect Model. This paper uses Data Panel on 27 Regencies and Cities in West Java Provinces from 2014 to 2016. This paper use Life expectancy as the dependent variable, health expenditure and number of poor people as the independent variable. The result shows that Pooled OLS, Fixed Effect Model and Random Effect Model estimate the health expenditure has a positive and significant effect on life expectancy in regencies and cities in West Java Provinces. Pooled OLS and Random Effect Model technique estimate number of poor people has a negative and significant effect on life expectancy in regencies and cities in West Java Provinces.

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Amaliah, Eka Nur, Darnah Darnah y Sifriyani Sifriyani. "Regresi Data Panel dengan Pendekatan Common Effect Model (CEM), Fixed Effect model (FEM) dan Random Effect Model (REM) (Studi Kasus: Persentase Penduduk Miskin Menurut Kabupaten/Kota di Kalimantan Timur Tahun 2015-2018)". ESTIMASI: Journal of Statistics and Its Application 1, n.º 2 (3 de julio de 2020): 106. http://dx.doi.org/10.20956/ejsa.v1i2.10574.

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Panel data regression is a regression that combines cross section data and time series data. Panel data regression estimation can be done through 3 estimates namely CEM, FEM and REM. This research will make a modeling of the percentage of poor people according to regencies / cities in East Kalimantan using panel data regression analysis. Poverty occurs due to lack of income and assets to meet basic needs. For this reason, variables that are assumed to affect the percentage of the poor are used, including the Population Growth Rate (LPP), Human Development Index (HDI), and Adjustable Per capita Expenditure (PPD). By using 3 CEM, FEM and REM approaches based on testing, the best FEM model is obtained. Based on the FEM model the factors that significantly influence are the HDI and PPD. A value of 0.7755 means that the HDI and PPD can explain the percentage of poor people according to the Regency / City in East Kalimantan of 77.55% while the remaining 22.45% is influenced by other variables not yet included in the model.

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Roy, Mili y Md Israt Rayhan. "Import Flows of Bangladesh: Gravity Model Approach under Panel Data Methodology". Dhaka University Journal of Science 60, n.º 2 (31 de julio de 2012): 153–57. http://dx.doi.org/10.3329/dujs.v60i2.11485.

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In counterpoint to export growth, Bangladesh import growth has remained much less strong, despite impressive progress in import liberalization. This study gives an overview of different methodologies related to gravity model analysis in Bangladeshs import flow. A pooled cross section and time series data were analyzed to incorporate the country specific heterogeneity in country pair trading partners. The import flows are justified by the basic gravity model since Bangladeshs imports are positively significant by the economy size and inversely related to trade barrier. Accordingly, we have analyzed pooled ordinary least square, fixed effect, random effect. This study also explores extended gravity model using several variables in the light of gravity model panel data approach. Bangladeshs import is determined by the home and foreign countrys gross domestic product and exchange rate. In addition, Cross section results show that regional trade arrangement which is South Asian Association for Regional Co-operation and border are significant for Bangladeshs importimplies that Bangladesh should import more from intra regional country and also should import from India.DOI: http://dx.doi.org/10.3329/dujs.v60i2.11485 Dhaka Univ. J. Sci. 60(2): 153-157, 2012 (July)

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Kipngetich, Samoei Ben, Joel Tenai y Andrew Kimwolo. "Effect of Operating Cash Flow on Stock Return of Firms Listed In Nairobi Security Exchange". Eastern Journal of Economics and Finance 6, n.º 1 (27 de agosto de 2021): 26–35. http://dx.doi.org/10.20448/809.6.1.26.35.

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The main aim of the paper was to establish the effect of operating cash flow on stock return of firms listed in NSE. The study was informed by Free Cash Flow (FCF) theory. Census survey was adapted to review financial statements for 29 listed non-financial firms at NSE that had consistent data for all the study variables. Secondary data was extracted for 12 years from 2007-2019 with the aid of a data collection sheet. Explanatory research design which is panel in nature was followed by this study. Both descriptive and inferential statistics were used in data analysis. Panel data regression was used to make inferences and test research hypothesis. Fixed and Random effects methods were used to analyze the balanced panel data using STATA statistical package and Hausman test established that Random effect model was the most ideal method to analyze data in this study. The findings indicated that operating cash flow positively and significantly influenced the stock returns for firms listed at NSE. The study concludes that operating cash flow information affects stock returns. Therefore, the study advocates for firms to increase their levels of operating cash flows through prudent utilization of cash resources since it enhances the stock returns.

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Indrasetianingsih, Artanti y Tutik Khalimatul Wasik. "MODEL REGRESI DATA PANEL UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI PULAU MADURA". Jurnal Gaussian 9, n.º 3 (30 de agosto de 2020): 355–63. http://dx.doi.org/10.14710/j.gauss.v9i3.28925.

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Poverty arises when a person or group of people is unable to meet the level of economic prosperity which is considered a minimum requirement of a certain standard of living or poverty is understood as a state of lack of money and goods to ensure survival. Panel data regression is the development of regression analysis which is a combination of time series data and cross section data. Panel data regression is usually used to make observations of data that is examined continuously for several periods. The purpose of this study is to determine the factors that influence the level of poverty in Madura Island in the period 2008 - 2017. In this study the variables used in this study are life expectancy (X1), average length of school (X2), level open unemployment (X3), and labor force participation (X4) with the Comman Effect Model (CEM) approach, Fixed Effect Model and Random Effect Model (REM). To choose the best model from the three is the chow test, the hausman test and the breusch-pagan test. In this study, the best model chosen was the Fixed Effect Model. Keywords: CEM, Fixed Effect Model, Data Panel Regression, REM, Poverty level.

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Olalekan, Lasisi Isiaka. "Effect of Liquidity Risk, Premium Growth on the Performance of Quoted Insurance Firms in Nigeria: A Panel Data Analysis". American Finance & Banking Review 2, n.º 1 (27 de enero de 2018): 42–51. http://dx.doi.org/10.46281/amfbr.v2i1.128.

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This study assesses the effect of liquidity risk on firm performance of listed insurance companies in Nigeria for the period of 2011-2015. The listed insurance firms are twenty Five (25) in numbers out of which a sample of twelve (12) were used for the study. Liquidity risk as the independent variable was proxy with leverage, claim loss ratio and premium growth, while the return on asset was used to proxy firm performance. The study adopts a panel multiple regression techniques and data were collected from secondary source through the annual reports of the firms after controlling for fixed/random effects.The findings of random effect reveal that leverage has significant negative effect on return on assets. The claim loss ratio has insignificant negative influence on return on assets while premium growth has positive and insignificant effect on firm performance of listed insurance companies in Nigeria. It is recommended among others that the managers, shareholders and other stake holders to checkmate and control liquidity risk as it have been found empirically to enhance the quality of the firm’s financial performance.

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Murdayanti, Yunika. "PENGUJIAN PECKING ORDER THEORY MENGGUNAKAN REGRESI DATA PANEL PADA INDUSTRI MAKANAN DAN MINUMAN". Media Riset Akuntansi, Auditing dan Informasi 7, n.º 1 (13 de abril de 2007): 39. http://dx.doi.org/10.25105/mraai.v7i1.970.

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The principal objective in this paper is to ascertain the extent to which Myers (1984) Pecking Order Theory (POT) of business financial appears to explain leverage amongst a pane! of 17 food and beverage companies, taken from Jakarta Stock Exchange during period 2003-2005. The analysis using Panel Data Regression and the research findings reported in the paperthat only profitability and growth significantly influence leverage using both OLS (Ordinary Least Square) and fixed effect. But with OLS, the result finding more significant than fixed effect and random effect. However, the findings also suggest the need for a modified POT that more fully reflects the spade cirazatances and nuances of food and beverage leverage especially when using between long term and short term debt. A full specification fora modified POTof leverage & food and beverage is proposed as a basis for further inquiry in the area.Keywords: pecking order theory, leverage, profitability, growth, size, age, asset

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Alamanda, Alamanda. "THE EFFECT OF ECONOMIC GROWTH ON INCOME INEQUALITY:PANEL DATA ANALYSIS FROM FIFTY COUNTRIES". INFO ARTHA 5, n.º 1 (30 de marzo de 2021): 1–10. http://dx.doi.org/10.31092/jia.v5i1.1176.

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The relationship between economic growth and income inequality is one of the controversial issues in macroeconomics. Many studies have been done to show the relationship between economic growth and income inequality. However, the research about this problem by using panel data is still minimum. Also, there is still no research that differentiates the effect between lower-middle, upper-middle, and high-income countries. This paper examines the effect of economic growth on income inequality by analysing a panel data set of fifty countries from 2000 to 2018. Using the Pooled OLS, Fixed Effect, and Random Effect Model, this paper finds that economic growth has a positive significant impact on income inequality, which means the higher the economic growth, the bigger the gap between the rich and the poor. The empirical evidence suggests that a one-point increase in GDP growth will increase the Gini Index by 0.082 to 0.085 points on average. Moreover, the paper finds that the effect of economic growth on increasing the incidence of income inequality seems to be higher in lower-middle and upper-middle income countries than in high-income countries.

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Du, Cong, Jie Shen, Xiuyan Liu y Meng Qin. "The Influence of Urban Sprawl on Household Power Intensity——Evidence from China's Urban Panel Data". E3S Web of Conferences 236 (2021): 01033. http://dx.doi.org/10.1051/e3sconf/202123601033.

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The paper measures the yearly urban sprawl index and household power intensity of 285 prefecture-level and Municipality cities in China from 2004 to 2017. Through the establishment of a fixed effect model, random effect model and systematic GMM model, this paper empirically analyze the impact of urban sprawl on household power intensity, and found that there is a significant and positive effect of urban sprawl on household power intensity, that is, the higher the urban sprawl, the lower the efficiency of household electricity energy utilization will be, and this effect has a cogent robustness. On this basis, the establishment of a mediating effect model found that population agglomeration playes a significant role of the partial mediating effect in the process of urban sprawl affecting household power intensity. The conclusion of this paper provides some policy implications for the scientific and reasonable urban planning in the process of urbanization in China from the perspective of optimizing household power intensity.

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Sri Herianingrum, Muhammad Sanusi, Haryo Firas Tunas Kuncoro,. "Makroekonomi dan Penanaman Modal Asing di Indonesia: Bukti Empiris di Pulau Jawa". Jurnal Ekonomi 24, n.º 2 (26 de septiembre de 2019): 288. http://dx.doi.org/10.24912/je.v24i2.592.

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Penanaman Modal Asing di Indonesia dipengaruhi oleh berbagai faktor. Tujuan utama penelitian ini adalah untuk mengetahui pengaruh variabel makroekonomi terhadap Penananaman Modal Asing (PMA) di Indonesia: Bukti Empiris di Pulau Jawa. Jenis data dalam penelitian ini adalah data panel yaitu data gabungan data runtun waktu (time series) tahunan dari 2010-2018, dan cross section berdasarkan jumlah provinsi di Pulau Jawa (DKI Jakarta, Banten, Jawa Barat, Jawa Tengah, Daerah Istimewa Yogyakarta, dan Jawa Timur). Metode yang digunakan adalah metode data panel dengan model fixed effect dan random effect. Untuk menentukan model yang akan digunakan dengan cara uji hausman. Dari uji hausman bahwa model yang baik untuk digunakan dalam penelitian ini adalah random effect model. Hasil penelitian menunjukkan bahwa variabel jumlah penduduk (populasi) berpengaruh positif signifikan terhadap penanaman modal asing (FDI). Variabel inflasi memiliki pengaruh negatif namun tidak signifikan terhadap FDI. Variabel pertumbuhan ekonomi (PDRB) memiliki pengaruh positif signifikan terhadap FDI, sedangkan untuk variabel upah memiliki pengaruh positif signifikan terhadap FDI.

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ALIFAH, AYU, HAZMIRA YOZZA y YUDIANTRI ASDI. "FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN DI KOTA/KABUPATEN PROVINSI SUMATERA BARAT DENGAN MENGGUNAKAN ANALISIS REGRESI PANEL". Jurnal Matematika UNAND 9, n.º 1 (29 de mayo de 2020): 53. http://dx.doi.org/10.25077/jmu.9.1.53-61.2020.

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Kemiskinan diartikan sebagai suatu keadaan dimana taraf hidup manusia berada pada keadaan serba kekurangan dan tidak mampu untuk memenuhi kebutuhan dasar. Salah satu cara untuk mengukur kemiskinan di suatu daerah adalah dengan menggunakan indikator persentase penduduk miskin di daerah tersebut. Provinsi Sumatera Barat merupakan salah satu daerah yang masih memiliki penduduk miskin dengan persentase yang cukup besar. Pemerintah Sumatera Barat berusaha untuk menekan persentase kemiskinan dari berbagai aspek yang terkait dengan faktor-faktor yang diperkirakan mempengaruhi angka kemiskinan. Data mengenai persentase penduduk miskin serta faktor-faktor yang diduga mempengaruhinya dikumpulkan Badan Pusat Statistik untuk semua daerah secara berkala, sehingga untuk semua daerah secara berkala, sehingga untuk masing-masing daerah tersedia data dari tahun ke tahun. Data pengamatan yang dikumpulkan untuk beberapa objek pengamatan dan untuk beberapa waktu itu disebut data panel. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi kemiskinan di Provinsi Sumatera Barat pada tahun 2015-2017 dengan menggunakan Analisis Regresi Panel. Pada penelitian ini diperoleh metode yang tepat digunakan adalah random effect model dengan faktor yang signifikan mempengaruhi persentase kemiskinan yaitu penduduk yang tamat SMA. Dari hasil penelitian ini, semakin tinggi persentase penduduk yang tamat SMA, maka semakin rendah persentase penduduk miskin.Kata Kunci: Data Panel, Analisis Regresi Panel, Random effect model

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Bekhet, Hussain A., Ahmad Mohammad Alsmadi y Mohamed Khudari. "Effects of Internal and External Factors on Profitability of Jordanian Commercial Banks: Panel Data Approach". International Journal of Financial Research 11, n.º 5 (5 de octubre de 2020): 359. http://dx.doi.org/10.5430/ijfr.v11n5p359.

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This article assesses the effects of internal and external factors on the profitability of Jordanian commercial banks. A panel data set of thirteen commercial banks between 2000 and 2018 was used. Pooled ordinary least squares, random and fixed models were applied. Moreover, a Hausman test was performed to confirm the suitability of models, which was preferred on the random effect model. Also, a Wooldridge test for serial correlation and a modified Wald test for groupwise Heteroskedasticity were used and both of their null hypotheses were rejected. However, to deal with these problems, a robustness analysis was performed using feasible generalized least square. The findings suggested that internal factors and in particular, bank size and diversification, had positive effects on bank profitability, while credit risk, operational risk and leverage risk were negatively related to bank performance. However, capital risk had a positive but insignificant impact on bank profitability. As for the effect of external factors, the results suggested that financial development and inflation had a positive and significant impact on bank profitability, while market concentration and stock market volatility had a significant negative effect on bank profitability. Further, a negative and insignificant impact were found for GDP and refugee crisis on bank profitability in Jordan. The findings would help managers of commercial banks, investors, government, policy makers and shareholders to make better decisions and improve performance by highlighting areas of weaknesses. In general, policy makers should become more aware with these insights on profit determinants in Jordanian commercial banks.

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Ramesh, Kandela. "Bad Loans of Public Sector Banks in India: A Panel Data Study". Emerging Economy Studies 5, n.º 1 (2 de abril de 2019): 22–30. http://dx.doi.org/10.1177/2394901519825911.

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The soundness of the banking system is necessary for economic advancement and financial stability. In the contemporary era, the Indian banking system has suffered from the accumulation of substantial non-performing assets (NPAs), especially in the public sector banks (PSBs). This article examines the financial determinants of bad loans in the Indian PSBs with the help of panel data regression analysis. Panel dataset of 21 Indian PSBs for eight years from 2010 to 2017 is used for the study. For analysis, net non-performing assets (NNPAs) as a dependent variable and financial indicators as independent variable are used. Using the random effect model, it is found that credit–deposit ratio, loan maturity, and return on assets have a negative relationship with NNPAs. These factors have an association with a lower level of NPAs. Operating expenses and capital adequacy ratio have an insignificant effect on NNPAs. On the other hand, factors such as priority sector loans, collateral values, and non-interest income have a positive impact on NNPAs. These factors are an indication of a higher level of bad loans and are adding to the accumulation of NPAs in PSBs.

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49

Abu-Lila, Ziad Mohammed. "A Panel Data Analysis of Jordan’s Foreign Trade: The Gravity Model Approach". International Journal of Economics and Finance 10, n.º 1 (15 de diciembre de 2017): 204. http://dx.doi.org/10.5539/ijef.v10n1p204.

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This study aims to identify the most important factors affecting the flow of Jordanian foreign trade, with its main trading partners for the period (1995-2016). To achieve this objective, the gravity model was adopted using a random effects model. The empirical findings show that Jordan’s foreign trade is positively determined by Jordan’s RGDP and dummy variable that used to capture the effect of a common border with Jordan. On the other side, distance and similarity index are found to be significant factors in influencing Jordanian foreign trade negatively. Finally, the study found that the RGDP of trade partner and bilateral real exchange rate are not statistically significant. empirical evidence linking bank customers’ participation in financial ads to their attitude. Managerially, this study informs bank managers regarding effective management of financial advert contents in order to influence bank customer’s attitude towards financial adverts.

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Hasibuan, Lailan Syafrina, Rahma Nurjanah y Etik Umiyati. "Faktor–faktor yang mempengaruhi inflasi Provinsi-Provinsi di Sumatera". e-Jurnal Perspektif Ekonomi dan Pembangunan Daerah 8, n.º 1 (4 de marzo de 2019): 1–14. http://dx.doi.org/10.22437/pdpd.v8i1.4899.

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This study aims to: 1) analyze inflationary developments, road infrastructure, government spending, provincial minimum wage, and economic growth provincial in Sumatra; 2) analyze the influence of road infrastructure, government spending, provincial minimum wage, and economic growth provincial in Sumatra. This research uses a descriptive analysis method to determine the development of each research variable and quantitative methods using panel data regression approach random effect. Based on the descriptive analysis of inflationary development, road infrastructure stagnated, government spending, provincial minimum wage, and economic growth was increased every year. The regression of panel data with random effect approach variable of the provincial minimum wage has a positive and significant influence on the inflation of provincial in Sumatra. While road infrastructure, government spending, economic growth have no significant effect on provincial inflation in Sumatra. Keywords: Inflation, Government spending, Economic growth.

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