Studying the Relationship between Stock Prices of Publicly Traded US Construction Companies and Gross Domestic Product: Preliminary Step toward Construction–Economy Nexus

2020 ◽  
Vol 146 (1) ◽  
pp. 04019087
Author(s):  
Islam H. El-adaway ◽  
Gasser G. Ali ◽  
Ibrahim S. Abotaleb ◽  
Herbert M. Barber
ProBank ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 17-21
Author(s):  
Heriyanta Budi Utama ◽  
Florianus Dimas Gunurdya Putra Wardana

The purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015. The sampling technique in this study using a purposive sampling. With the technique of purposive  sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression. The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share priceThe purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015.The sampling technique in this study using a purposive sampling. With the technique of purposive  sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression.The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share price


Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Rajesh Vedanthan ◽  
Mondira Ray ◽  
Valentin Fuster ◽  
Ellen Magenheim

Introduction: Hypertension is the leading global risk for mortality and its prevalence is increasing in many low- and middle-income countries. Hypertension treatment rates are low worldwide, potentially in part due to insufficient human resources. However, the relationship between health worker density and hypertension treatment rates is unknown. Objective: To conduct an econometric analysis of the relationship between health worker density and hypertension treatment rates worldwide. Methods: Hypertension treatment rates were collected from published reports between 1980 and 2010. Data on health worker (physician and nurse) density were obtained from the World Health Organization (WHO). Data for potential confounding variables--per capita gross domestic product, hospital bed density, burden of infectious diseases, land area and urban population--were obtained from WHO and World Bank databases. Potential interaction by per capita gross domestic product was evaluated. Multivariable logistic-logarithmic regression analysis was performed using Stata. Results: Full data were available from 146 countries spanning all World Bank income classification categories. Health worker density was significantly associated with hypertension treatment rate in the unadjusted model (beta = 0.23; p < 0.005). In the fully adjusted model, the association remained positive but was not statistically significant (beta = 0.30; p = 0.078) (Figure). Hypertension treatment rates were more strongly related to physician than nurse density (beta = 0.21 vs 0.08; p = 0.10 vs 0.49). Conclusion: Hypertension treatment rates across the world appear to be related to health worker density, although the relationship does not achieve strict statistical significance. Our results suggest that a 10% increase in health worker density is associated with a 2-3% increase in hypertension treatment rate. Given the global burden of hypertension and other chronic diseases, WHO guidelines for health workforce staffing may need to be reconsidered.


2014 ◽  
Vol 1 (3) ◽  
pp. 156-162
Author(s):  
Tendai Makoni

The time series yearly data for Gross Domestic Product (GDP), inflation and unemployment from 1980 to 2012 was used in the study. First difference of the logged data became stationary as suggested by the time series plots. Johansen Maximum Likelihood Cointegration test indicated a long-run relationship among the variables. Granger Causality tests suggested unidirectional causality between inflation and GDP, implying that GDP is Granger caused by inflation in Zimbabwe. Another unidirectional causality was noted between unemployment and inflation. The causality between unemployment and inflation imply that unemployment do affect GDP indirectly since unemployment influences inflation which in turn positively affect GDP.


Author(s):  
Joan Mwihaki Nyika

Climate change is the greatest challenge of the modern day with the capacity to destabilize global financial systems and socioeconomic welfare. This chapter explores the uncertainties posed by climate change, its effects on the economy, the risks associated with the phenomenon, and approaches to manage them through risk management. Using documented evidence, climate change is shown to result in gross domestic product reductions; physical, transition, and liability risks that result to systemic financial problems characterized by liquidation of companies, losses for, and closure of financial firms and their intermediaries; and inability of investors to pay debts. Climate risk management is proposed as a solution to adapt to climate change and reduce its associated risks.


2017 ◽  
Vol 9 (10) ◽  
pp. 145 ◽  
Author(s):  
Bibi Rouksar-Dussoyea ◽  
Ho Ming-Kang ◽  
Raja Rajeswari ◽  
Benjamin Chan Yin-Fah

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.


Author(s):  
Karen A. Rasler ◽  
William R. Thompson

A central cleavage in the war making-state making literature is between advocates of the notion that warfare has been the principal path to developing stronger states and critics who argue that the relationship no longer holds, especially in non-European contexts. It is suggested that the problem is simply one of theoretical specification. Increasingly intensive warfare, as manifested in European combat, made states stronger. Less intensive warfare, particularly common after 1945, is less likely to do so. Empirical analysis of a more representative data set on state capacity (revenues as a proportion of gross domestic product [GDP]), focusing on cases since 1870, strongly supports this point of view. The intensiveness of war is not the only factor at work—regime type and win/loss outcomes matter as well—but the relationship does not appear to be constrained by the level of development.


Author(s):  
Najid Ahmad ◽  
Muhammad Farhat Hayat ◽  
Muhammad Luqman ◽  
Shafqat Ullah

This paper investigates the relationship between foreign direct investment and economic growth in Pakistan. The co-integration and error correction model is used to show the relationship between foreign direct investment and gross domestic product in Pakistan. Gross domestic product is taken as dependent variable while foreign direct investment, labor force and domestic capital as independent variables. The results suggest that there is a positive relation between foreign direct investment and gross domestic product in short as well as long run. If we want to make economic progress then there is a need to invite foreign investors because foreign direct investment increases GDP that is economic growth.


2018 ◽  
Vol 4 ◽  
pp. 237802311877362 ◽  
Author(s):  
Xiaorui Huang ◽  
Andrew K. Jorgenson

The authors examine the potentially asymmetrical relationship between economic development and consumption-based and production-based CO2 emissions. They decompose economic development into economic expansions and contractions, measured separately as increases and decreases in gross domestic product per capita, and examine their unique effects on emissions. Analyzing cross-national data from 1990 to 2014, the authors find no statistical evidence of asymmetry for the overall sample. However, for a sample restricted to nations with populations larger than 10 million, the authors observe a contraction-leaning asymmetry whereby the effects of economic contraction on both emissions outcomes are larger in magnitude than the effects of economic expansion. This difference in magnitude is more pronounced for consumption-based emissions than for production-based emissions. The authors provide tentative explanations for the variations in results across the different samples and emissions measures and underscore the need for more nuanced research and deeper theorization on potential asymmetry in the relationship between economic development and anthropogenic emissions.


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