A Time-Series Analysis of the Relationship Between Government Expenditure and Gdp in Canada

1991 ◽  
Vol 19 (3) ◽  
pp. 316-333 ◽  
Author(s):  
Panayiotis C. Afxentiou ◽  
Apostolos Serletis
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Noha Hesham Ghazy ◽  
Hebatallah Ghoneim ◽  
Dimitrios Paparas

Purpose One of the main theories regarding the relationship between government expenditure and gross domestic product (GDP) is Wagner’s law. This law was developed in the late-19th century by Adolph Wagner (1835–1917), a prominent German economist, and depicts that an increase in government expenditure is a feature often associated with progressive states. This paper aims to examine the validity of Wagner’s law in Egypt for 1960–2018. The relationship between real government expenditure and real GDP is tested using three versions of Wagner’s law. Design/methodology/approach To test the validity of Wagner in Egypt, law time-series analysis is used. The methodology used in this paper is: unit-root tests for stationarity, Johansen cointegration approach, error-correction model and Granger causality. Findings The results provide strong evidence of long-term relationship between GDP and government expenditure. Moreover, the causal relationship is found to be bi-directional. Hence, this study provides support for Wagner’s law in the examined context. Research limitations/implications It should be noted, however, that there are some limitations to this study. For instance, in this paper, the government’s size was measured through government consumption expenditure rather than government expenditure due to data availability, which does not fully capture the government size. Moreover, the data available was limited and does not fully cover the earliest stages of industrialization and urbanization for Egypt. Furthermore, although time-series analysis provides a more contextualized results and conclusions, the obtained conclusions suffer from their limited generalizability. Originality/value This paper aims to specifically make a contribution to the empirical literature for Wagner’s law, by testing the Egyptian data using time-series econometric techniques for the longest time period examined so far, which is 1960–2018.


1980 ◽  
Vol 17 (4) ◽  
pp. 470-485 ◽  
Author(s):  
Dominique M. Hanssens

The author's principal objective is to present a framework for market analysis which specifically models primary demand, competitive reaction, and feedback effects of the market variables. The approach is an extension of earlier work by Clarke and by Lambin, Naert, and Bultez on the relationship among the elasticities of the marketing variables. The author develops this framework and formulates an approach for empirical applications based on principles of time series analysis. In particular, Granger's well-known causality definition is used in conjunction with Box-Jenkins analysis to find the nonzero elements in the marketing model. These principles are applied empirically to the case of a city pair of the U.S. domestic air travel market, where three major airlines compete on the basis of flight scheduling and advertising. The analysis reveals that flight scheduling has a market-expansive or a competitive effect, depending on the competitor, and that advertising does not have a significant impact on performance. In addition, several patterns of competitive reactions are found. The author offers observations on the theoretical and empirical aspects of this approach to marketing model building.


2014 ◽  
Vol 47 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Marko Grdešić

This article uses a mixed-methods approach to analyze the relationship between television and protest during East Germany’s revolution. The content of television newscasts, both West German and East German, is analyzed together with protest event data. There are two key findings. First, West German coverage of protests is associated with an increase in protest in the first phase of the revolution. This finding emerges from time series analysis. Second, West German and East German television coverage were interacting, with the latter reacting to the former. This finding emerges from both quantitative and qualitative analysis.


2004 ◽  
Vol 61 (2) ◽  
pp. 176-183 ◽  
Author(s):  
G. Gudmundsson

Abstract Catch-at-age analysis provides estimates of stock size at ages when the fish have reached catchable size. Survey indices contain information about relative cohort size at younger ages. The present analysis is concerned with survey indices of juveniles up to the youngest age where stock estimates, based on time-series analysis of catch-at-age data, are available. A stock estimate at that age from catch-at-age data is also included. A common model of the relationship between stock size and survey indices is combined with the model describing the decline of a stock by natural mortality. Random variations in natural mortality are defined separately from sampling variations and irregular catchability in the survey. The stock size and magnitudes of the random variations are estimated by the Kalman filter, which also provides predictions of future recruitment to the catchable stock. Analysis of observations of Icelandic cod reveals a large deviation from proportionality in the relationship between the index and the stock estimates in the youngest ages, but haddock data are compatible with proportionality. Variations in natural mortality during the second to fourth year of cod and the second to third year of haddock are not a major factor in variations of stock size.


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