scholarly journals The Determinants of Global Competitiveness of Economy: A Dynamic Panel Approach Applied to the WAEMU Countries

2020 ◽  
Vol 6 (2) ◽  
pp. 16
Author(s):  
Moussa Sigue
Keyword(s):  
Significant Contribution ◽  
Generalized Method Of Moments ◽  
Economic Openness ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Global Competitiveness ◽  
Panel Model ◽  
The Subject ◽  
Internal Absorption

This paper examines the determinants of the global competitiveness of the WAEMU economy applying a dynamic panel approach from 2011 to 2017. After providing a synthesis of the both theoretical and empirical debates on the subject, we derived a dynamic panel model which estimation was reached using the system generalized method of moments (GMM). The result of the estimation shows that competitiveness lagged by one period, financial development, GDP per capita, internal absorption and foreign trade taxes positively and significantly affect the global competitiveness of WAEMU countries, while economic openness, the inflation rate and the quality of institutions have a negative and significant contribution.

scholarly journals The determinants of the global competitiveness of the economy: a dynamic panel approach applied to the WAEMU country

2020 ◽  
Author(s):  
Moussa SIGUE
Keyword(s):  
Financial Development ◽  
External Pressure ◽  
Commercial Policy ◽  
Economic Openness ◽  
Dynamic Panel ◽  
Global Competitiveness ◽  
Quality Of Institutions ◽  
Generalized Moments ◽  
Internal Absorption

Abstract This article examines the determinants of the overall competitiveness of the WAEMU economy from a dynamic panel approach over the period 2011–2017. The estimate by the method of generalized moments in system (GMM) Reveled that the delayed competitiveness of a period financial development, GDP per head, internal absorption and taxes on foreign trade affects positively and significantly the overall competitiveness of the WAEMU countries while economic openness, the rate of inflation and the quality of institutions have contributed negative and significant. It emerges from this work that an improvement in the overall competitiveness of the Union's economy imperatively requires accelerating the process of development of quality, the financial system as well as protecting local industries from external pressure to through a more adequate commercial policy taking into account the constraints linked to commercial agreements.

scholarly journals Regional differences in the capitalisation of first and second pillar payments of the CAP into land rental prices

2020 ◽  
Author(s):  
Klaus Salhofer ◽  
Paul Feichtinger
Keyword(s):  
Agricultural Policy ◽  
Regional Differences ◽  
Dynamic Panel ◽  
Accounting Data ◽  
Dynamic Panel Model ◽  
Panel Model ◽  
Land Rental ◽  
Part Time ◽  
High Yields ◽  
Large Farms

Abstract Nearly 80 per cent of Common Agricultural Policy (CAP) expenditures are spent on three different measures: first pillar payments (FPPs), agri-environmental payments (AEPs) and less favoured area payments (LFAPs). Based on a dynamic panel model and farm accounting data for Bavaria, we find that, on average, 30 per cent of FPPs, 40–50 per cent of LFAPs, but no relevant share of AEPs are capitalised into land rental prices. The capitalisation ratio varies considerably across regions. Above average capitalisation ratios for FPPs are observed in more favourable areas with high yields, a low grassland share and large farms. The same is true for LFAPs for areas with high yields, large farms and a greater share of part-time farmers.

scholarly journals X-Differencing and Dynamic Panel Model Estimation

2010 ◽  
Author(s):  
Chirok Han ◽  
Peter C. B. Phillips ◽  
Donggyu Sul
Keyword(s):  
Model Estimation ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Panel Model

scholarly journals Does Climate Change Mitigation Activity Affect Crude Oil Prices? Evidence from Dynamic Panel Model

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Jude C. Dike
Keyword(s):  
Climate Change ◽  
Crude Oil ◽  
Climate Change Mitigation ◽  
Oil Prices ◽  
Carbon Intensity ◽  
Dynamic Panel ◽  
Dynamic Panel Model ◽  
Panel Model ◽  
Crude Oil Prices ◽  
Change Mitigation

This paper empirically investigates how climate change mitigation affects crude oil prices while using carbon intensity as the indicator for climate change mitigation. The relationship between crude oil prices and carbon intensity is estimated using an Arellano and Bond GMM dynamic panel model. This study undertakes a regional-level analysis because of the geographical similarities among the countries in a region. Regions considered for the study are Africa, Asia and Oceania, Central and South America, the EU, the Middle East, and North America. Results show that there is a positive relationship between crude oil prices and carbon intensity, and a 1% change in carbon intensity is expected to cause about 1.6% change in crude oil prices in the short run and 8.4% change in crude oil prices in the long run while the speed of adjustment is 19%.

Impact of Macroeconomic Factors on Cash Holdings?: A Dynamic Panel Model

2018 ◽  
Vol 17 (1_suppl) ◽  
pp. S27-S53 ◽  
Author(s):  
Lalita Anand ◽  
M. Thenmozhi ◽  
Nikhil Varaiya ◽  
Saumitra Bhadhuri
Keyword(s):  
Exchange Rate ◽  
Cash Holdings ◽  
Oil Price ◽  
Oil Price Shocks ◽  
Stock Market Index ◽  
Price Shocks ◽  
Dynamic Panel ◽  
Macroeconomic Factors ◽  
Dynamic Panel Model ◽  
Panel Model

We examine if macroeconomic factors impact cash holdings and how it influences the speed of adjustment of cash to target levels using the Arellano-Bover/Blundell-Bond dynamic panel model. We analyse a balanced panel and find that exchange rate, stock market index and oil price shocks impact cash holdings positively. We also observe that firms hold more cash in expectation of GDP growth, oil price shocks, increase in credit spread, budget deficit and hold marketable securities in expectation of inflationary conditions in the economy, while they hold less cash in expectation of an increase in exchange rate and increase in long-term and short-term bond rates. We further substantiate that cash holdings in firms adjust to target cash reserves in a dynamic process. We provide strong evidence that macroeconomic policy decisions impact cash levels in firms.

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