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 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.

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 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 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 influence of economic policy uncertainty and geopolitical risk on US citizens overseas air passenger travel by regional destination

2020 ◽  
pp. 135481662098119
Author(s):  
James E Payne ◽  
Nicholas Apergis
Keyword(s):  
Economic Policy ◽  
Forecast Error ◽  
Error Variance ◽  
Variance Decomposition ◽  
Air Travel ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Passenger Travel ◽  
Forecast Error Variance

This research note extends the literature on the role of economic policy uncertainty and geopolitical risk on US citizens overseas air travel through the examination of the forecast error variance decomposition of total overseas air travel and by regional destination. Our empirical findings indicate that across regional destinations, US economic policy uncertainty explains more of the forecast error variance of US overseas air travel, followed by geopolitical risk with global economic policy uncertainty explaining a much smaller percentage of the forecast error variance.

Sign in / Sign up

Export Citation Format

Share Document