scholarly journals The Determinants of Services Sector Growth: A Comparative Analysis of Selected Developed and Developing Economies

2018 ◽  
Vol 57 (1) ◽  
pp. 27-44
Author(s):  
Muhammad Salam ◽  
Javed Iqbal ◽  
Anwar Hussain ◽  
Hamid Iqbal
Keyword(s):  
Panel Data ◽  
Developing Economies ◽  
Panel Data Analysis ◽  
Trade Openness ◽  
Dynamic Panel Data ◽  
Services Sector ◽  
Panel Data Estimation ◽  
The Common ◽  
Data Estimation ◽  
Dynamic Panel Data Estimation

This study empirically examines the possible factors that determine the services sector growth, both in selected developed and developing economies. For estimation purpose, the study employs the static as well as the dynamic panel data estimation technique with panel data over the period 1990-2014. The results suggest that GDP per capita, FDI net inflow, trade openness and innovations are the common factors that significantly affect the services sector growth both in developed and in developing economies. However, the productivity gap is the only factor that does not have any significant impact on services sector growth, both in developed and developing economies, which indicates that the Baumol's cost disease has been cured. Keywords: Services Sector Growth, Panel Data Analysis, Innovations

scholarly journals The Dynamic Effects of Innovation, FDI, & Trade Liberalization on Services Sector: An Evidence from Developed and Developing Economies

2020 ◽  
Vol 8 (2) ◽  
pp. 116-132
Author(s):  
Muhammad Chishti ◽  
◽  
Farrukh Mehmood ◽  
Keyword(s):  
Trade Liberalization ◽  
Developing Economies ◽  
Trade Openness ◽  
Dynamic Panel Data ◽  
Dynamic Effects ◽  
Services Sector ◽  
Panel Data Estimation ◽  
Productivity Differential ◽  
Data Estimation

The current study is a bid to explore the dynamic effects of Innovation, FDI, and trade openness on services sector in selected developed and developing economies for the period of 1992 to 2016. For computing the empirical findings, this study deploys the static as we all dynamic panel data estimation approaches. The results reveal the significant role of GDP per capita and FDI in the growth of services sector. However, the services sector incurs the detrimental repercussions on the account of trade liberalization. These findings also demonstrate that, in both samples of economies, the services sector does not respond to the productivity differential. Furthermore, innovation exhibits a significant association with the growth of services sector in the case of developing economies.

scholarly journals Dynamic panel data estimation of an integrated Grossman and Becker–Murphy model of health and addiction

2018 ◽  
Vol 56 (2) ◽  
pp. 703-733 ◽  
Author(s):  
Andrew M. Jones ◽  
Audrey Laporte ◽  
Nigel Rice ◽  
Eugenio Zucchelli
Keyword(s):  
Panel Data ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Panel Data Estimation ◽  
Data Estimation ◽  
Dynamic Panel Data Estimation

scholarly journals DETERMINANTS OF BANK COST EFFICIENCY: EMPIRICAL EVIDENCE FROM BANGLADESH

2020 ◽  
Author(s):  
Israth Sultana ◽  
Mohammad Morshedur Rahman
Keyword(s):  
Panel Data ◽  
Cost Efficiency ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Capital Adequacy ◽  
Operating Costs ◽  
Dynamic Panel ◽  
Panel Data Estimation ◽  
Data Estimation ◽  
Dynamic Panel Data Estimation

Due to the trust of depositors, banks should be responsible for efficient utilization of resources to achieve cost efficiency (CE) which in turn contributes to raising income. Previous studies found that the average CE of banks in Bangladesh was around 80%. This study aims to find the determinants of CE in Bangladesh from a sample of 33 banks during a period from 2009 to 2016. Stochastic Frontier Approach (SFA) was used to measure CE in the first stage. In the second stage, different types of regression estimations were used like pooled ordinary least square, fixed effect or random effect panel regression, System-Dynamic Panel Data Estimation and Arellano-Bond Dynamic Panel Data Estimation for comparison. The results showed that Generalized Method of Moments (GMM) specifically the Arellano-Bond Dynamic Panel Data Estimation was best suited for problems of endogeneity, serial correlation, heteroskedasticity and cross sectional dependence in data The results revealed that regulatory capital, risk measured by non-performing loan ratio, liquidity measured by total loans to total deposits, and level of operating costs had a significant negative impact on CE. In contrast, lagged cost efficiency, profitability, years of operation, net interest income had a significant positive impact on CE. To attain competitive advantage by performing with higher CE, policymakers should focus on capital regulation measured by capital adequacy ratio, risk level, profit earning capacity, aggressiveness of banks, bank size, years of operation and level of operating costs.  

scholarly journals Linear Dynamic Panel-data Estimation Using Maximum Likelihood and Structural Equation Modeling

2018 ◽  
Vol 18 (2) ◽  
pp. 293-326 ◽  
Author(s):  
Richard Williams ◽  
Paul D. Allison ◽  
Enrique Moral-Benito
Keyword(s):  
Maximum Likelihood ◽  
Panel Data ◽  
Structural Equation ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Equation Modeling ◽  
Dynamic Panel ◽  
Panel Data Estimation ◽  
Data Estimation ◽  
Dynamic Panel Data Estimation

Panel data make it possible both to control for unobserved confounders and to include lagged, endogenous regressors. However, trying to do both simultaneously leads to serious estimation difficulties. In the econometric literature, these problems have been addressed by using lagged instrumental variables together with the generalized method of moments, while in sociology the same problems have been dealt with using maximum likelihood estimation and structural equation modeling. While both approaches have merit, we show that the maximum likelihood–structural equation models method is substantially more efficient than the generalized method of moments method when the normality assumption is met and that the former also suffers less from finite sample biases. We introduce the command xtdpdml, which has syntax similar to other Stata commands for linear dynamic panel-data estimation. xtdpdml greatly simplifies the structural equation model specification process; makes it possible to test and relax many of the constraints that are typically embodied in dynamic panel models; allows one to include time-invariant variables in the model, unlike most related methods; and takes advantage of Stata's ability to use full-information maximum likelihood for dealing with missing data. The strengths and advantages of xtdpdml are illustrated via examples from both economics and sociology.

scholarly journals Exchange Rate Volatility and Domestic Consumption: A Comparative Study of Developed, Developing and Emerging Economies

2019 ◽  
Vol 9 (3) ◽  
pp. 164
Author(s):  
Muhammad Zubair Chishti ◽  
Hafiz Syed Muhammad Azeem ◽  
Farrukh Mahmood ◽  
Adeel Ahmed Sheikh
Keyword(s):  
Exchange Rate ◽  
Panel Data ◽  
Developing Economies ◽  
Exchange Rate Volatility ◽  
Domestic Consumption ◽  
Aggregate Consumption ◽  
Developed Economies ◽  
Panel Data Estimation ◽  
The Exchange Rate ◽  
Data Estimation

The current study endeavors to explore the effects of oscillations in the exchange rate on the household aggregate consumption of developed, emerging, and developing economies, employing the panel data from 1995 to 2017. To select an appropriate panel data estimation technique, we apply Brush-Pagan & Hausman Tests for each set of chosen economies. Further, our study deduces that, in the case of developed economies, the oscillations in the exchange rate, significantly, affect the domestic consumption, supporting Alexander’s (1952) conjecture. However, in the case of emerging and developing economies, aggregate consumption does not respond to the exchange rate volatility.

BEYOND CONVENTIONAL TRADE: TRADE OPENNESS IMPLICATIONS OF TRADE IN VALUE ADDED

2020 ◽  
pp. 1-23
Author(s):  
HALIT YANIKKAYA ◽  
ABDULLAH ALTUN
Keyword(s):  
Negative Impact ◽  
Trade Openness ◽  
Value Added ◽  
Dynamic Panel Data ◽  
Growth Effect ◽  
Panel Data Estimation ◽  
Export Shares ◽  
Value Added Measures ◽  
Data Estimation ◽  
Trade In Value Added

This study compares the impacts of gross trade openness measures with trade openness in value-added measures on economic growth for the years 1995–2014 by employing a dynamic panel data estimation. Our findings suggest that although gross trade shares promote growth, using value-added trade shares magnifies this positive effect. Compared with gross terms, estimates also imply that while exports in value-added terms have much larger growth effect, imports in value-added terms have no significant impact. We then evaluate the impacts of tariffs on growth in terms of gross trade and trade in value added separately. Although our results imply the negative growth effects of gross import tariffs, this negative impact disappears for tariffs in value-added terms. These results reaffirm that trade protectionism has potential to lower global growth through reducing exports because it is clear that export shares regardless of their measurements and disaggregation levels promote growth. Our results indicate that countries should support not only exports of final products but also exports of intermediates. However, given the necessity of imports for exports, our results do not lend any evidence to discourage overall imports.

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