Income Inequality and Status Symbols: The Case of Fine Wine Imports

2019 ◽  
Vol 14 (4) ◽  
pp. 365-373 ◽  
Author(s):  
Britta Niklas ◽  
Elkhan Richard Sadik-Zada
Keyword(s):  
Income Inequality ◽  
The United States ◽  
Term Effect ◽  
Short Term ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Nonlinear Autoregressive ◽  
Jel Classifications ◽  
Analyze Data

AbstractThis survey investigates the inequality-fine wine imports nexus. To this end, the study employs cointegration techniques to analyze two panel datasets, one of which will analyze data from 12 countries between 1871 and 2018, and another that analyzes data from 66 countries between 1995 and 2017. Estimations indicate that income inequality leads to more fine wine imports in the long run. Changes in income have only a short-term effect on fine wine imports. Nonlinear autoregressive distributed lag (NARDL) estimators reveal an asymmetric long-run relationship between income inequality and fine wine imports in the cases of Argentina and the United States. (JEL Classifications: C19, D01, D12, D31, L66)

scholarly journals ANALISIS DETERMINANT PROFITABILITAS PADA INDUSTRI PERBANKAN SYARIAH PERIODE 2011-2018 PENDEKATAN AUTO REGRESIVE DISTRIBUTED LAG (ARDL)

2020 ◽  
Vol 7 (6) ◽  
pp. 1102
Author(s):  
Gita Martha Permatasari ◽  
Dian Filianti
Keyword(s):  
Sampling Method ◽  
Banking Industry ◽  
Secondary Data ◽  
Short Term ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Analysis Technique ◽  
Lag Model

This study aims to determine the influence of the Macro Economy, namely GDP and Inflation and Bank Characteristics, namely CAR, FDR, NPF, BOPO and Size on the Profitability of the Sharia Banking Industry in Indonesia in the 2011 - 2018 Period. The data used are secondary data, namely quarterly data obtained from the official website of Bank Indonesia (www.bi.go.id), Badan Pusat Statistik (www.bps.go.id), and Statistik Perbankan Syariah reports published by OJK (www.ojk.go.id). The sampling method used was purposive sampling method. The analysis technique uses the ARDL (Autoregressive Distributed Lag) model with statistical tools EViews 9. The results of the study show that in the short term of the GDP, Inflation, BOPO, Size variables, they have a significant effect on the profitability of the Sharia Banking Industry and the CAR, FDR, NPF variables have no significant effect on profitability of Islamic Banking Industry. Meanwhile in the long run of the GDP, BOPO, Size variables, they have a significant effect on the profitability of the Sharia Banking Industry and the Inflation, CAR, FDR, NPF variable does not significantly influence the profitability of the Sharia Banking Industry.Keywords: Profitability, Sharia Bank, ARDL

scholarly journals Investigating the Income Inequality in Indonesia: An Application of Autoregressive Distributed Lag Approach

2021 ◽  
Vol 2 (4) ◽  
pp. 184-193
Author(s):  
Zulfa Nazli ◽  
Abd. Jamal ◽  
Muhammad Nasir
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Income Inequality ◽  
Urban Population ◽  
Skills Training ◽  
Short Term ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Short And Long Term

This study investigates the effect of economic growth, urban population, unemployment, and human capital on income inequality in Indonesia. Annual data collected from World Development Indicator (WDI) is used from 1984 to 2019. The analytical method of this research is Autoregressive distributed lag (ARDL) to examine the short and long-term relationships. The results show that economic growth positively and significantly affects income inequality in the short and long term. The urban population variable has a significant negative effect in the short term but not in the long term. The unemployment variable has a significant positive effect in the long run. Finally, human capital negatively affects the short term while not in the long term. Based on these findings, it is recommended that the government stabilize inequality by increasing progressive taxes, creating jobs, providing soft skills training beyond formal education, and socializing the concept of commuter work.

scholarly journals Stock Market Investment and Inflation: Evidence from the United States and Canada

2021 ◽  
Vol 13 (3) ◽  
pp. 339-365
Author(s):  
Janesh Sami
Keyword(s):  
United States ◽  
Stock Market ◽  
Stock Prices ◽  
The United States ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Goods Market ◽  
Stock Market Investment ◽  
Robust Evidence

This paper examines the long-run relationship between goods prices and stock prices to understand whether stock market investment can help hedge against inflation in the United States (US) and Canada. This study employed an autoregressive distributed lag (ARDL) cointegration test developed by Pesaran, Shin, and Smith (2001), and finds evidence of a positive long-run economic relationship between stock prices and goods prices in both economies over the sample period 1960 to 2019. The long-run elasticity is above one for both economies implying that the developments in the goods market significantly affect the stock market. We undertake a suite of sensitivity checks and find robust evidence that the stock market investment can help hedge against inflation in the United States and Canada.

Exports and Inequality: Evidence from the Highly Concentrated Textile and Garment Sector of Bangladesh

2021 ◽  
pp. 097317412110248
Author(s):  
Md. Iqbal Bhuyan ◽  
Keun-Yeob Oh
Keyword(s):  
Income Inequality ◽  
Time Series Data ◽  
Threshold Level ◽  
Series Data ◽  
High Concentration ◽  
Bounds Testing ◽  
Export Sector ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run

In this study, we investigate the effects of textile and garment (T&G) exports on income inequality in Bangladesh. Focusing on T&G exports alone, which contribute more than 90% of the country’s total exports, we hypothesize that the export sector of a country being concentrated on a single industry widens income inequality. Based on time series data over the period 1991–2015, the autoregressive distributed lag (ARDL) bounds testing approach to cointegration indicates that there is a long-run relationship between the variables. It seems that exports from the T&G sector have a statistically significant effect on income inequality in the long run, such that the high concentration of T&G exports contributes to widening income inequality in Bangladesh. This result implies that policies oriented toward export diversification are necessary so that people working in other sectors can also engage in income generating activities from exports. Our results also demonstrate that income inequality rises in the initial stages of economic growth. Then, after reaching a threshold level of growth, income inequality falls. This result confirms the validity of the Kuznets hypothesis in the case of Bangladesh.

scholarly journals ASYMMETRY IN THE STOCK PRICE RESPONSE TO MACROECONOMIC SHOCKS: EVIDENCE FROM THE KOREAN MARKET

2018 ◽  
Vol 19 (2) ◽  
pp. 343-359 ◽  
Author(s):  
Geul Lee ◽  
Doojin Ryu
Keyword(s):  
Nonlinear Model ◽  
Stock Price ◽  
Macroeconomic Shocks ◽  
Macroeconomic Variables ◽  
Price Response ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Korean Market ◽  
Nonlinear Autoregressive

This study investigates stock price movements in response to macroeconomic shocks, allowing for asymmetry in this relationship. Given Ferson’s (1989) finding that large and small stocks can exhibit different risk behaviors, we examine the behaviors of the KOSPI and KOSDAQ stock markets in response to changes in the price level, real interest rate, and real USD/KRW exchange rate using simple and nonlinear autoregressive-distributed lag (ARDL) models. We find that the long-run effects of macroeconomic shocks are relatively insignificant under the simple ARDL model, whereas a significant and negative long-run effect is found for almost every explanatory variable–market pair under the nonlinear model. In addition, we find that the long-run effects of stock price shocks on macroeconomic variables are more significant under the nonlinear model. Overall, the results imply that it is difficult to identify the relationship between macroeconomic variables and stock price dynamics without considering asymmetry.

scholarly journals A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of the FTSE and S&P500 Indexes

Risks ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 195
Author(s):  
David Allen ◽  
Michael McAleer
Keyword(s):  
Weak Form ◽  
Stationary Time Series ◽  
Bounds Testing ◽  
Distributed Lag ◽  
Price Series ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Quantile Regression Analysis ◽  
The Impact ◽  
Nonlinear Autoregressive

The paper features an examination of the link between the behaviour of the FTSE 100 and S&P500 Indexes in both an autoregressive distributed lag ARDL, plus a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a daily FTSE adjusted price series, commencing in April 2009 and terminating in March 2021, and a corresponding daily S&P500 Index adjusted-price series obtained from Yahoo Finance. The data period includes all the gyrations caused by the Brexit vote in the UK, beginning with the vote to leave in 2016 and culminating in the actual agreement to withdraw in January 2020. It was then followed by the impact of the global spread of COVID-19 from the beginning of 2020. The results of the analysis suggest that movements in the contemporaneous levels of daily S&P500 Index levels have very significant effects on the behaviour of the levels of the daily FTSE 100 Index. They also suggest that negative movements have larger impacts than do positive movements in S&P500 levels, and that long-term multiplier impacts take about 10 days to take effect. These effects are supported by the results of quantile regression analysis. A key result is that weak form market efficiency does not apply in the second period.

scholarly journals Asymmetric effects of rainfall on food crop prices: evidence from Rwanda

2017 ◽  
Vol 8 (3) ◽  
pp. 137-149 ◽  
Author(s):  
Aimable Nsabimana ◽  
Olivier Habimana
Keyword(s):  
Empirical Investigation ◽  
Global Climate ◽  
Food Crop ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Crop Varieties ◽  
Long Run ◽  
Short Run ◽  
Food Affordability ◽  
Nonlinear Autoregressive

This study examined the effects of the likely change in rainfall on food crop prices in Rwanda, a landlocked country where agriculture is mainly rain-fed. The empirical investigation is based on nonlinear autoregressive distributed lag cointegration framework, which incorporates an error correction mechanism and allows estimation of asymmetric long-run and short-run dynamic coefficients. The results suggest that food crop prices are vulnerable to rainfall shocks and that the effect is asymmetric in both the short and long run. Moreover, there was evidence of seasonal differences, with prices falling during harvest season and rising thereafter. Considering the ongoing threat of global climate change, and in order to cope with rainfall shortage and uncertainty, increase food affordability and ultimately ensure food security throughout the year, there is a need to develop and distribute food crop varieties and crop technologies that reduce the vulnerability of farming to rainfall shocks.

scholarly journals Symmetric and asymmetric effects of financial development on carbon dioxide emissions in Nigeria: Evidence from linear and nonlinear autoregressive distributed lag analyses

2020 ◽  
Vol 38 (5) ◽  
pp. 2059-2078 ◽  
Author(s):  
Philip C Omoke ◽  
Silva Opuala-Charles ◽  
Chinazaekpere Nwani
Keyword(s):  
Carbon Dioxide ◽  
Financial Development ◽  
Carbon Dioxide Emissions ◽  
Asymmetric Effects ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Linear And Nonlinear ◽  
The Impact ◽  
Nonlinear Autoregressive

This study examines the impact of financial development on carbon dioxide emissions in Nigeria over the period 1971–2014. Income per capita, energy consumption, exchange rate and urbanization are incorporated in the analysis. The empirical analysis based on linear and nonlinear autoregressive distributed lag techniques provides evidence of long-run relationship among the variables in Nigeria. The results in general show that financial development has significant asymmetric effects on carbon dioxide emissions in Nigeria. Both short-run and long-run analyses show that the impact of positive changes in financial development on carbon dioxide emissions is significantly different from that of negative changes. The results suggest that in Nigeria positive shocks in financial development have significant reducing effect on carbon dioxide emissions, while negative shocks in financial development have significant increasing effect on carbon dioxide emissions. The empirical results also show that the response of carbon dioxide emissions to negative shocks in financial development is stronger. Based on these findings, this study concludes that mitigation policies would need to incorporate strategies to strengthen the depth of financial intermediation in the Nigerian economy.

A NEW LOOK AT THE REMITTANCES-FDI- ENERGY-ENVIRONMENT NEXUS IN THE CASE OF SELECTED ASIAN NATIONS

2019 ◽  
pp. 1-19 ◽  
Author(s):  
ZIA UR RAHMAN ◽  
HONGBO CAI ◽  
MANZOOR AHMAD
Keyword(s):  
Sri Lanka ◽  
Energy Use ◽  
The Philippines ◽  
Short Term ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Energy Environment ◽  
Negative Effect ◽  
India And China

This study investigates the association between remittances, FDI, energy use, and CO2 emissions for a sample of the top six Asian nations receiving remittances, namely, China, India, the Philippines, Pakistan, Bangladesh, and Sri Lanka, during the 1982–2014 period. The results of employing an autoregressive distributed lag (ARDL)-bound technique signify that there is a stable long-run association among the stated variables. The empirical findings indicate that CO2 increases significantly with a rise in energy use in all sample nations in both the long and short-runs. Conversely, the association between CO2 emissions and remittances is found to be significantly positive for Sri Lanka, Pakistan, the Philippines, and Bangladesh in the long-run, positive for Pakistan, the Philippines, and Sri Lanka only in the short-term, and non-significant for India and China in both the long and short-runs. Furthermore, the empirical results illustrate that the inflow of FDI significantly increases CO2 emissions in the cases of China, Sri Lanka, and India in both the long and short-runs. While FDI inflow has no significant effect on CO2 emissions for the Philippines and Pakistan, it has a significant negative effect for Bangladesh in both the long and short-runs. Thus, the connection between remittances, FDI, and CO2 emissions varies significantly across the countries considered in our study.

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