scholarly journals Stock Returns, Inflation and the “Reverse Causality” Hypothesis

2015 ◽  
Vol 4 (1) ◽  
pp. 32-50
Author(s):  
Mercy Ada Anyiwe ◽  
Sunday Osahon Igbinedion
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Forecast Error ◽  
Error Variance ◽  
Impulse Response Functions ◽  
Reverse Causality ◽  
Vector Error Correction ◽  
Vector Error ◽  
Forecast Error Variance ◽  
Causality Hypothesis

This paper attempts to empirically examine the Reverse Causality hypothesis within the Nigerian context during the period 1980 – 2011. Employing Vector Error Correction Methodology (VECM), causality was found between inflation and government stocks, with causality running from government stocks to inflation, thus providing evidence in support of the reverse causality hypothesis. The results from the forecast error variance decomposition (FEVD) and impulse response functions tend to further lend credence to this finding. Accordingly, this study suggests, in part, the need for a tight monetary policy which would help to reduce inflation and stock prices, as such measures would leave the individuals with less money to buy stocks. Such efforts should be complemented by augmenting domestic production and encouraging investment through inexpensive bank finance. 

scholarly journals An Empirical Study of Dividend Payout and Future Earnings in Singapore

2010 ◽  
Vol 13 (02) ◽  
pp. 267-286 ◽  
Author(s):  
King Fuei Lee
Keyword(s):  
Forecast Error ◽  
Error Variance ◽  
Response Analysis ◽  
Causality Test ◽  
Dividend Payout ◽  
Vector Error Correction ◽  
Future Earnings ◽  
Vector Error ◽  
Long Run ◽  
Forecast Error Variance

The main purpose of this paper is to apply Johansen's vector error-correction model (VECM) to investigate the existence of the dividend signalling effect in the Singapore aggregate market through impulse response analysis, forecast error variance decomposition and Granger-causality test. Our findings show that a unit shock increase in dividend payout leads to a permanent increase in future earnings over time. These results imply that there exists informational/signalling content in dividend payout in the Singapore market over the long run. We further find that at least half of the forecast error variance in earnings can be accounted for by innovations in the dividend payout. In addition, the payout ratio is also shown to Granger-cause earnings in the Singapore market.

scholarly journals Examining the Relationship between Diffrent Modes of Infrastructure Financing and Economic Growth in India

2019 ◽  
Vol 8 (4) ◽  
pp. 8677-8684
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Forecast Error ◽  
Error Variance ◽  
Public And Private ◽  
Vector Error Correction ◽  
Dynamic Relationship ◽  
Vector Error ◽  
Forecast Error Variance ◽  
The Impact

With an aim to achieve a status of 5 trillion economy, India has to fulfil the criteria of achieving minimum 9%+ growth rate consistently for next five years. But at present, the economic indicators of India reflect a dismal picture to achieve that goal. The economic growth rate of India has gone down to almost five percent in first quarter of financial year 2019-20. Since the opening up of the Indian economy in 1991, the role of private sector in reviving the country’s growth cannot be overstated. Expanding investment in infrastructure is often projected as a weapon which can play a counter cyclical role in the phase of such economic crisis. In an attempt to analyse the impact different modes of investment in infrastructure on economic growth of India, this paper examines the trend of investments by private as well as both public and private (joint) since 1990s. Further, a time series econometric analysis is carried out for a period of twenty-eight years (1990-2018) wherein the nexus between investments (primarily in transportation and energy sector) and economic growth of India (GDP per capita) is examined. To examine the dynamic relationship between the variables, their causality, exogeneity and comparability, the Vector auto regression (VAR) model, along with the Forecast Error Variance Decomposition (FEVD) and Vector Error Correction Model (VECM) is used. The results of VAR and VECM suggests that there is significant impact of investment in infrastructure upon economic growth of India.

THE PRICE OF COCAINE AND THE COLOMBIAN PESO: AN EMPIRICAL INVESTIGATION

2019 ◽  
Vol 19 (03) ◽  
pp. 1950015
Author(s):  
ALEXI THOMPSON ◽  
YAYA SISSOKO
Keyword(s):  
Forecast Error ◽  
Control Policy ◽  
Error Variance ◽  
Decomposition Methods ◽  
Nominal Exchange Rate ◽  
Policy Implications ◽  
Vector Error Correction ◽  
National Drug ◽  
Forecast Error Variance ◽  
National Drug Control Policy

While the underground economy is not explicitly included in the measure of (GDP), the cocaine trade has been a major source of revenue for Colombia. Using quarterly cocaine prices from 1982 to 2007 published by the Office of National Drug Control Policy, this paper uses vector error correction and forecast error variance decomposition methods to look at the relationship between cocaine prices and the peso/$ nominal exchange rate. Our results indicate cocaine prices affect the value of the Colombian peso, which leads to some interesting policy implications.

scholarly journals Macroeconomic Variables and Stock Returns Revisited

2020 ◽  
Vol 03 (10) ◽  
Author(s):  
Feifei Wang ◽  
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Explanatory Power ◽  
Macroeconomic Factors ◽  
Vector Error Correction ◽  
Macroeconomic Variables ◽  
The Real ◽  
Vector Error ◽  
Long Run ◽  
Short Run

I revisit the relation between macroeconomic activities and stock prices by selecting the most important macroeconomic variables that are appropriate for analyzing their impact on stock returns. Using vector autogressive models (VAR), combined with co integration analysis and the vector error correction model (VECM) I estimate the explanatory power of each macroeconomic variable on the variations of the stock prices and distinguish the short-run from long-run movements among all key macroeconomic variables. I find that (1) in the short-run macroeconomic variables do not appear help explain changes in stock returns, (2) in the long-run the real interest rate and industrial production are the most important macroeconomic factors, and (3) in the long-term the real economic activity and stock returns Granger-cause each other.

scholarly journals Interlinkages among Asian, European and the U.S Stock Markets: A Multivariate Cointegration Analysis

2012 ◽  
Vol 4 (3) ◽  
pp. 129-141 ◽  
Author(s):  
P. Sakthivel
Keyword(s):  
Error Correction ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Markets ◽  
Cointegration Analysis ◽  
Vector Error Correction ◽  
Vector Error ◽  
Integration Test ◽  
The Us ◽  
The Impact

The present study attempts to investigate the dynamic interlinkages among the Asian, European and US stock markets. Daily closing prices of twelve stock indices relating to the period from 3rd January 1998 to 30th June 2010 and are used in the analysis. Both short and long run relationships are examined through Johansen-Juselius co integration and Vector Error Correction models (VECM) and Impulse Response Function (IRF). The results of the co integration test show strong co integration relationship across international stock prices indices. The results of the Vector Error Correction model reveal that the US and some of European and Asian Stock markets lead the Indian stock market. Finally, the evidence suggests that the impact of the US market on Indian stock returns is much higher than other way round.

scholarly journals Impact of credit risk and profitability on liquidity shocks of Namibian banks: an application of the structural VAR model

2021 ◽  
Vol 8 (3) ◽  
pp. 349-359
Author(s):  
Albert V. Kamuinjo ◽  
Ravinder Rena ◽  
Andrew Maredza
Keyword(s):  
Credit Risk ◽  
Granger Causality ◽  
Impulse Response ◽  
Forecast Error ◽  
Error Variance ◽  
Variance Decomposition ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Liquidity Shocks ◽  
Forecast Error Variance

The main purpose of this paper was to investigate the relationship between banks’ credit risk and profitability and liquidity shocks in Namibia for the period 2009 to 2018 using the SVAR model. In estimating the SVAR regression model, granger causality, impulse-response functions and forecast error variance decomposition were employed and evaluated. The sample consisted of Namibian commercial banks. By auditing liquidity data between 2009 and 2018, empirical results showed that liquidity risk is caused by a combination of structural shocks. The granger causality, impulse-response functions and forecast error variance decomposition documented that credit risk (non-performing loans) is key factor affecting liquidity conditions in Namibia in the medium to long run. In addition, the empirical results showed that quality earnings (ROA) have minimal impact on liquidity conditions in the short run. Reforming assets quality policies and earnings quality policies can be valuable policy tools to minimize liquidity shortages and avoid insolvent banks in Namibia.

scholarly journals Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship

Mathematics ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 774 ◽  
Author(s):  
David ◽  
Inácio ◽  
Tenreiro Machado
Keyword(s):  
Forecast Error ◽  
Error Variance ◽  
Price Transmission ◽  
Data Series ◽  
Agricultural Commodities ◽  
Vector Error Correction ◽  
Important Player ◽  
Forecast Error Variance ◽  
Price Relationship ◽  
Johansen Cointegration Test

Brazil is an important player when it comes to biofuel and agricultural production. The knowledge of the price relationship between these markets has increasing importance. This paper adopts several tools, namely the Bai–Perron test of breakpoints, the Johansen cointegration test and the vector error correction model exploited by the orthogonal impulse response and the forecast error variance decomposition, for investigating the price transmission among the ethanol and the main Brazil’s agricultural commodities (sugar, cotton, arabica coffee, robusta coffee, live cattle, corn and soybean). The data series cover the period from January 2011 up to December 2018. The results suggest a stronger price transmission from the ethanol commodity to the agricultural commodities, rather than the opposite situation.

Stock Market and Macroeconomic Behavior

2016 ◽  
Vol 5 (2) ◽  
pp. 12-30 ◽  
Author(s):  
Nabila Nisha
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Stock Returns ◽  
Stock Prices ◽  
Empirical Studies ◽  
Macroeconomic Factors ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error ◽  
Highly Sensitive

An impressive body of research has documented that movement in stock prices are highly sensitive to changes in the macroeconomic variables of an economy. Past empirical studies have examined this relationship across different stock markets by either outlining the influence of only domestic factors or a few global variables. A recent phenomenon has been the shift of academic interest to the emerging economies to investigate this presumed linkage by focusing more on global factors due to the trend of globalization. The aim of this paper is therefore to examine the influence of only global macroeconomic factors upon stock returns in the emerging stock market of Pakistan. By employing Vector Error Correction Model (VECM), findings indicate that significant influence of the global macroeconomic factors of the international interest rates and the world price index is observed, which implies a gradual integration of KSE towards the global financial markets. Limitations and implications for practice and research are also discussed.

Panel evidence of the dynamics between energy consumption and trade openness in ASEAN and East Asia

2021 ◽  
pp. 0958305X2110075
Author(s):  
Chee-Hong Law ◽  
Siok Kun Sek
Keyword(s):  
Energy Consumption ◽  
Forecast Error ◽  
Trade Openness ◽  
Error Variance ◽  
Capital Formation ◽  
Impulse Response Functions ◽  
Cross Sectional ◽  
Forecast Error Variance ◽  
Cross Sectional Dependence ◽  
Per Capita

This paper investigated the dynamics between trade openness and energy consumption in five members of the Association of Southeast Asian Nations (ASEAN) and three East Asian countries from 1980 to 2014. Previous theoretical discussions and empirical findings pointed out that trade openness had ambiguous effects on energy consumption. A panel dataset involving energy consumption per capita, trade openness, real gross domestic product per capita, gross fixed capital formation per capita and foreign direct investment was estimated. The Lagrange multiplier (LM) cross-sectional dependence test confirms the existence of cross-sectional dependence among the cross-sectional units. Moreover, the Westerlund cointegration test showed that the variables were not cointegrated. Hence, the dynamics among the variables were explored using the panel vector autoregressive method. The results suggested that there is a unidirectional Granger causality from trade openness to energy consumption. Further, the impulse response functions implied that the effect of trade openness on energy consumption occurred via the dynamics between trade openness and gross capital formation per capita. Finally, the forecast error variance decomposition showed that the contribution of trade openness on energy consumption increased during the examined period.

Estimating Orthogonal Impulse Responses via Vector Autoregressive Models

1991 ◽  
Vol 7 (4) ◽  
pp. 487-496 ◽  
Author(s):  
Helmut Lütkepohl ◽  
D.S. Poskitt
Keyword(s):  
Time Series ◽  
Forecast Error ◽  
Error Variance ◽  
Asymptotic Distributions ◽  
Impulse Response Functions ◽  
Impulse Responses ◽  
Vector Autoregressive ◽  
Forecast Error Variance ◽  
Variance Decompositions ◽  
The Relationship

Impulse response functions from time series models are standard tools for analyzing the relationship between economic variables. The asymptotic distribution of orthogonalized impulse responses is derived under the assumption that finite order vector autoregressive (VAR) models are fitted to time series generated by possibly infinite order processes. The resulting asymptotic distributions of forecast error variance decompositions are also given.

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