scholarly journals Inflation and Bank Credit

2022 ◽  
Vol 51-1 ◽  
pp. 1-21
Author(s):  
Miguel Ángel Tinoco-Zermeño ◽  
Víctor Hugo Torres-Preciado ◽  
Francisco Venegas-Martínez
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Dynamic Models ◽  
Dynamic Panel Data ◽  
Bank Credit ◽  
Negative Effects ◽  
Long Run ◽  
Inflation Rates ◽  
Short Run ◽  
Macroeconomic Stability

e objective of this paper is to assess empirically the effects of inflation rates on bank credit using panel data of the 32 Mexican states during 2003-2015. Our research method utilizes static models (pooled OLS, fixed effects, and random effects) and dynamic models (mean group, pooled mean group, and dynamic fixed effects) to analyze the relationship in the short and long runs. e main empirical result indicates that inflation rates exert negative effects on credit in the long run, but those effects tend to be positive in the short run. Concerning originality and findings, few papers study inflation and bank credit under macroeconomic stability, or in the case of Mexico with static and dynamic panel data models. However, one research limitation is the lack of data to apply the methodology before 1999 when inflation rates used to be higher. is would be useful to compare macroeconomic stability with instability.

Does tourism promote economic growth? A fractionally integrated heterogeneous panel data analysis

2021 ◽  
pp. 135481662098066
Author(s):  
Jorge V Pérez-Rodríguez ◽  
Heiko Rachinger ◽  
María Santana-Gallego
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Dynamic Panel Data ◽  
European Countries ◽  
Tourist Destinations ◽  
Contemporaneous Correlation ◽  
Long Run ◽  
Interactive Fixed Effects

In this article, we analyse whether tourism promotes economic growth using a general dynamic panel data model that incorporates individual and interactive fixed effects and allows for contemporaneous correlation in model innovations. The empirical study is based on quarterly series of GDP and tourist arrivals for 14 European countries covering the period from 1995 to 2019. Results indicate that the case for a positive long-run relationship between tourism and economic growth is rather weak, being slightly stronger for the period prior to the global economic and financial crisis from 2007 to 2010. When applying panel fractional cointegration techniques, we find evidence in favour of the tourism-led growth hypothesis (TLGH) for the full sample mainly for North European countries. For the pre-crisis period, on the other hand, we find evidence in favour of the TLGH for the relevant tourist destinations Spain and France.

scholarly journals Dinamika PMA dan PMDN di Indonesia Sebagai Dampak Dari Upah Minimum, Inflasi dan PDRB Tahun 2004-2012: Pendekatan Dynamic Panel Data Model

2016 ◽  
Vol 17 (3) ◽  
pp. 119
Author(s):  
Lea Widowati Sugiharto ◽  
Akhmad Syakir Kurnia
Keyword(s):  
Panel Data ◽  
Minimum Wage ◽  
Direct Investment ◽  
Dynamic Panel Data ◽  
Wage Setting ◽  
Dynamic Panel ◽  
Explanatory Variables ◽  
Long Run ◽  
Short Run ◽  
Wage Increases

<div><em>This paper aims at investigating the behavior of foreign direct investment (FDI) and domestic direct investment (DDI) in Indonesia, which is expected to be explained by several explanatory variables including the setting of regional minimum wage, inflation, as well as regional domestic product. More specifically, the investigation is focused on the effect of annual increase in the minimum regional wage, provided that it is a sensitive issue for investors. Using 33 provincial level data in a period from 2004 to 2012, this paper uses a dynamic panel data which allows us to see the behavior of direct investment in the short run as well as in the long run. The result shows that an increase in the regional minimum wage setting reduces both DDI and FDI in the short run. However, in the long run, an increase in the regional minimum wage is likely to increase both DDI and FDI. This is likely indicating that in the long run an increase in wage is expected to be accompanied by higher productivity, eventhough in the short run higher wage increases cost of production which will undermine investment.</em></div>

Transformed-likelihood estimators for dynamic panel models with a very small T

2020 ◽  
pp. 1-20
Author(s):  
Mark Pickup ◽  
Vincent Hopkins
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Fixed Effects ◽  
Dynamic Models ◽  
Dynamic Panel ◽  
Panel Models ◽  
Long Run ◽  
Individual Effects ◽  
Lagged Dependent Variable ◽  
Dynamic Panel Models

Conventional OLS fixed-effects and GLS random-effects estimators of dynamic models that control for individual-effects are known to be biased when applied to short panel data (T ≤ 10). GMM estimators are the most used alternative but are known to have drawbacks. Transformed-likelihood estimators are unused in political science. Of these, orthogonal reparameterization estimators are only tangentially referred to in any discipline. We introduce these estimators and test their performance, demonstrating that the unused orthogonal reparameterization estimator in particular performs very well and is an improvement on the commonly used GMM estimators. When T and/or N are small, it provides efficiency gains and overcomes the issues GMM estimators encounter in the estimation of long-run effects when the coefficient on the lagged dependent variable is close to one.

scholarly journals Analysis of the New Kuznets Relationship: Considering Emissions of Carbon, Methanol, and Nitrous Oxide Greenhouse Gases—Evidence from EU Countries

2021 ◽  
Vol 18 (6) ◽  
pp. 2907
Author(s):  
Mara Madaleno ◽  
Victor Moutinho
Keyword(s):  
Nitrous Oxide ◽  
Least Squares ◽  
Fixed Effects ◽  
Ghg Emissions ◽  
Ordinary Least Squares ◽  
Kuznets Curve ◽  
Ekc Hypothesis ◽  
Long Run ◽  
Short Run ◽  
The Eu

Decreased greenhouse gas emissions (GHG) are urgently needed in view of global health threat represented by climate change. The goal of this paper is to test the validity of the Environmental Kuznets Curve (EKC) hypothesis, considering less common measures of environmental burden. For that, four different estimations are done, one considering total GHG emissions, and three more taking into account, individually, the three main GHG gases—carbon dioxide (CO2), nitrous oxide (N2O), and methane gas (CH4)—considering the oldest and most recent economies adhering to the EU27 (the EU 15 (Old Europe) and the EU 12 (New Europe)) separately. Using panel dynamic fixed effects (DFE), dynamic ordinary least squares (DOLS), and fully modified ordinary least squares (FMOLS) techniques, we validate the existence of a U-shaped relationship for all emission proxies considered, and groups of countries in the short-run. Some evidence of this effect also exists in the long-run. However, we were only able to validate the EKC hypothesis for the short-run in EU 12 under DOLS and the short and long-run using FMOLS. Confirmed is the fact that results are sensitive to models and measures adopted. Externalization of problems globally takes a longer period for national policies to correct, turning global measures harder and local environmental proxies more suitable to deeply explore the EKC hypothesis.

Determinants of total factor productivity in Visegrad Group Nuts-2 regions

2018 ◽  
Vol 68 (1) ◽  
pp. 31-50 ◽  
Author(s):  
Barbara Danska-Borsiak
Keyword(s):  
Panel Data ◽  
Total Factor Productivity ◽  
Latent Variables ◽  
Fixed Effects ◽  
Orthogonal Transformation ◽  
Common Factors ◽  
Dynamic Panel Data ◽  
Factor Productivity ◽  
The Common ◽  
Visegrad Group

This article attempts to estimate the total factor productivity (TFP) for 35 NUTS-2 regions of the Visegrad Group countries and to identify its determinants. The TFP values are estimated on the basis of the Cobb-Douglas production function, with the assumption of regional differences in productivity. The parameters of the productivity function were analysed with panel data, using a fixed effects model. There are many economic variables that influence the TFP level. Some of them are highly correlated, and therefore the factor analysis was applied to extract the common factors – the latent variables that capture the common variance among those observed variables that have similar patterns of responses. This statistical procedure uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. Each component is interpreted using the contributions of variables to the respective component. I estimated a dynamic panel data model describing TFP formation by regions. An attempt was made to incorporate the common factors among the model’s explanatory variables. One of them, representing the effects of research activity, proved to be significant.

The Association Between Bank Credit Terms and Conditions and the Business Cycle in the Euro Area

2019 ◽  
Vol 65 (4) ◽  
pp. 247-256
Author(s):  
Dimitrios Anastasiou ◽  
Konstantinos Drakos
Keyword(s):  
Business Cycle ◽  
Euro Area ◽  
Bank Loan ◽  
Bank Credit ◽  
Monetary Policies ◽  
Policy Makers ◽  
Long Run ◽  
Loan Terms ◽  
Short Run ◽  
The Business Cycle

Abstract We explored the trajectory of bank loan terms and conditions over the business cycle, where the latter was decomposed into its long-run (trend) and short-run (cyclical) components. We found that deterioration of each business cycle component leads to a significant tightening of credit terms and conditions. We found mixed results concerning the symmetry of impacts of the short and long run components. Symmetry was found between the terms and conditions on loans for small vs. large enterprises. Our findings provide very useful information to policy makers and should be taken into consideration when monetary policies are designed.

NON-LINEAR EFFECTS OF TERRORISM ON ECONOMIC GROWTH IN PAKISTAN: ACCOUNTING FOR CAPITAL PER WORKER AND STRUCTURAL BREAKS

2019 ◽  
pp. 1950014
Author(s):  
RONALD RAVINESH Kumar ◽  
SYED JAWAD HUSSAIN SHAHZAD ◽  
PETER JOSEF STAUVERMANN ◽  
NIKEEL Kumar
Keyword(s):  
Economic Growth ◽  
Capita Income ◽  
Structural Breaks ◽  
Per Capita Income ◽  
Negative Effects ◽  
Capital Share ◽  
Long Run ◽  
Non Linear ◽  
Short Run ◽  
Per Capita

In this study, we examine the asymmetric effects of terrorism and economic growth in Pakistan over the period 1970–2016, while considering the role of capital per worker and structural breaks. We use the non-linear ARDL approach to establish the long-run association and to estimate the short-run and long-run effects accordingly. The results indicate the presence of asymmetries in both long and short run. Moreover, 1% decrease in terrorism results in an increase of per capita income by 0.02% in the long run and 0.001% in the short run. Assuming symmetry, the long run capital share is 0.47. In asymmetric relation, a 1% increase in capital share increases output by 0.55%, whereas a 1% decrease in capital stock decreases output by 0.26%. The break effects show that the years 1993 and 2004 have negative effects on growth. The vector error correction model-based causality results indicate a unidirectional causality from terrorism to per capita income. Overall, the results highlight that terrorism is growth retarding.

Linkages Between Employment and Net FDI Inflow: Insights from Individual as Well as Panel Data for Emerging South Asian Labour Market

2020 ◽  
pp. 097215091987350
Author(s):  
Ramesh Chandra Das ◽  
Kamal Ray
Keyword(s):  
Panel Data ◽  
Error Correction ◽  
Labour Market ◽  
South Asian ◽  
Wald Test ◽  
Individual Country ◽  
Employment Level ◽  
Long Run ◽  
Short Run ◽  
Per Capita

In emerging labour market, particularly, the direct and indirect association between employment level and foreign direct investment (FDI) in a dynamic economy is non-deniable. Like private and public investments, FDI promotes employment generating agenda and at the same time, sound employment scenario of an economy attracts FDI to inflow. Under this backdrop, the present study attempts to examine whether employment and net FDI inflow have long-run associations and short-run dynamics in South Asian economies for the period 1991–2016. Applying cointegration and Granger causality tests for individual country level and panel cointegration, vector error correction and Wald test on the two standardized variables—employment–population ratio and per capita net FDI inflow—reveal that the two indicators have cointegrating relations for Bangladesh and Nepal and FDI makes a cause to employment generation in Bangladesh only. Further, the panel data exercise shows the existence of long-run or equilibrium relations linking the two indicators without significant error correction results. The Wald test results show that there is short-run causality working from employment ratio to per capita FDI and vice versa. The study, thus, prescribes for ensuring quality environment in the concerned domestic economies of the region so that employment opportunities invite FDI inflow to their territories.

Assessing the effects of flight delays, distance, number of passengers and seasonality on revenue

Kybernetes ◽  
2019 ◽  
Vol 48 (9) ◽  
pp. 2138-2149
Author(s):  
Murat Guven ◽  
Eyup Calik ◽  
Basak Cetinguc ◽  
Bulent Guloglu ◽  
Fethi Calisir
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Future Research ◽  
Negative Effects ◽  
Flight Delays ◽  
Content Type ◽  
Positive Effects ◽  
Common Correlated Effects ◽  
Flight Delay ◽  
Airline Company

Purpose This study aims to investigate the effects of flight delays, distance, number of passengers and seasonality on revenue in the Turkish air transport industry. Design/methodology/approach The domestic return routes of a Turkish airline company were examined to address this issue. Among five cities and six airports, 14 major domestic return routes were selected. The augmented mean group (AMG) estimator and common correlated effects mean group (CCEMG) estimator were conducted with a two-way fixed effects (FE) robustness test in this study. Findings The results show that arrival flight delay and departure flight delay had negative effects on revenue, whereas the distance between airports, the number of air passengers and seasonality had positive effects on revenue. Research limitations/implications The data used in this study were retrieved from a Turkish airline company; for future research, other airline companies operating in Turkey may be included. Practical implications These findings could be evaluated by air transportation leaders to provide a guide to make strategic decisions to achieve greater performance in this competitive environment. Originality/value The originality of the paper comes from the facts that besides distance and number of passengers, the authors control for the seasonality when assessing the effects of flight delay on revenue; they use panel data techniques, which permit them to control for individual heterogeneity, and create more variability, more efficiency and less collinearity among the variables; they use two recent panel data techniques, CCEMG and AMG, allowing for cross-section dependence.

scholarly journals Bias correction methods for dynamic panel data models with fixed effects

2017 ◽  
Vol 6 (2) ◽  
pp. 58
Author(s):  
Mohamed Abonazel
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Estimation Methods ◽  
Time Dimension ◽  
Dynamic Panel ◽  
Cross Sectional ◽  
Cross Sectional Dimension ◽  
Ls Estimator

This paper considers the estimation methods for dynamic panel data (DPD) models with fixed effects, which suggested in econometric literature, such as least squares (LS) and generalized method of moments (GMM). These methods obtain biased estimators for DPD models. The LS estimator is inconsistent when the time dimension (T) is short regardless of the cross-sectional dimension (N). Although consistent estimates can be obtained by GMM procedures, the inconsistent LS estimator has a relatively low variance and hence can lead to an estimator with lower root mean square error after the bias is removed. Therefore, we discuss in this paper the different methods to correct the bias of LS and GMM estimations. The analytical expressions for the asymptotic biases of the LS and GMM estimators have been presented for large N and finite T. Finally; we display new estimators that presented by Youssef and Abonazel [40] as more efficient estimators than the conventional estimators.

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