The Application of Cointegration Method for Structural Data in the Estate Market Analysis

The article touches upon the topical issues of the residential real estate market, which are proposed to be solved by means of time series cointegration. The study aims to assess the structure of the housing market by types of apartments using price dynamics per one square meter of apartments' total area. The objectives of the study are to develop a methodology of determination of time series cointegration for the data with structural relationships; to analyze the average prices for the types of apartments on the primary and secondary housing market; to study the housing market in the Russian Federation by quarterly data of state statistics for the period 2000–2020 based on the developed methodology.The results of the research showed that the prices at the primary and secondary housing market by types of apartments do not always represent an integrated process of the frst order and cannot be used for building a co-integration equation. This necessitated additional analysis and, as a consequence, the correction of the time period. It was proposed to ensure stationarity of linear combination of nonstationary data corresponding to the integrated process of the frst order by using the generalized least squares method (GLS). The sum of the elements of the cointegrating vector obtained this way tends to unity, and the elements themselves are estimates of the relative indi cators of the structure by types of apartments on the primary and secondary housing markets respectively. Thus, the suggested methodology allows estimating, on average, the share of the sold apartments of each type in the period under consideration, both in the regional context and in the country as a whole.The proposed methodology can be used for the estimation of relative indicators of the structure according to temporal data in different applications.

Determinants of Budget Deficit in Nigeria

This paper investigates the factors governing the determination of budget deficit in Nigeria from 1981q1 through 2016q4. Our methodology is based on Johansen cointegration and Vector Error Correction model (VECM) approach. The result from the Johansen cointegration test suggests one cointegrating vector, which indicates the existence of a long run cointegrating relationship. Evidence from the long run and short run parameters suggest that exchange rate, interest rate and one year lag of budget deficit are the major determinants of budget deficit. Therefore, to achieve a realistic fiscal surplus, the government should determine a high level of accountability in its fiscal operations. In addition, any fiscal surplus should be channeled into productive investments to diversify the economy and reduce the likelihood of potential budget deficits.

Service Sector as an Engine of Growth: Empirical Analysis of Rwanda

This research was econometrically analyzing Service sector as an engine of growth: empirical analysis of Rwanda from 1995 to 2020. The data were collected from BNR and were analyzed using Eviews7. The study used different opinions of economists concerning the Philips curve, by constructing short-term and long-term Philips curves in Rwanda by making some conclusions about the results at the end. We pay special attention in our research to the study of Phillips curve made by some economists of the last period the findings of this study indicate the following results: *, ** and *** indicates rejection of the null hypothesis of unit root at 10, 5% and 1% significant level, respectively. The SERV, FDI, LR, GR series are not stationary at level, and then we should test the Stationarity at the first difference. (*), (**) & (***) represent respectively 10%, 5% and 1% level of significance.The results give an indication for the existence of long-run relationship between SERV and growth. The max and trace values statistic strongly reject the null hypothesis for “none “cointegration vector in favor of at least one cointegrating vectors at the 1 percent significance level. The cointegrating vector representing the long run relationship between service and growth. The above is endogenous because its probability of chi-square 0.000025 is less than 5% level of significance and it answers the second hypothesis of a Variable that can help national bank of Rwanda to control money supply in the short-run.The P- value of chi-square which is 0.0791 and this is greater than 0, 05 level of significant therefore, there is no short run causality between variables running from SERV, FDI, LR and GR at 5% level of significant. The results revealed out from the above table; LSERV, LFDI, LLR and LGR does Granger Cause LSERV at 10% level of significant due to their probability of 0.0284 which is less than 0.10 level of significance but LSERV does not Granger Cause LSERV, LFDI, LLR and LGR at 10% level of significant due to their probability of 0.1224 which is greater than 0.10 level of significance.

On the determinants of data breaches: A cointegration analysis

Cyber risks and particularly data breaches constitute one of the new frontiers of risk modeling for insurers across the world. We use the cointegration methodology to uncover the relation between data breaches and Bitcoin-related variables. We perform our analyses on two different datasets of data breaches. In both cases, we provide statistical evidence of a bidirectional lead–lag relation in the short run between the variables under investigation. Moreover, the existence of a cointegrating vector suggests that this relation is likely to persist in the long run. To evaluate the quantitative implications of the relations found, we complement the study with Granger causality tests, impulse response analyses and variance decompositions of the forecasting errors.

Multivariate Analysis on the Effectiveness of Monetary and Fiscal Policies in Fiji

By utilising a Cointegrating Vector Autoregressive Model, this paper assesses the relative effectiveness the fiscal and monetary policies on growth. It is observed that government expenditure has the strongest effect on Fiji’s national income which significantly explains Fiji’s GDP error variance even after a three year period with regard to the effect of shocks, we observed that the national income impulse respons to the one standard error shock among all macroeconomic variables, i.e. government expenditure and foreign assets, which is not permanent but transitory.

The Economic Impact of Road Accidents: The Case of Sri Lanka

The purpose of this study is to disclose accident-related indices and investigate the extent to which the road accidents impact on the economic performance of Sri Lanka during the period from 1977 to 2016. Annual time-series data are used to evaluate the accident indices for econometric analysis. Augmented Dickey–Fuller (ADF) unit root analysis and Johansen’s maximum likelihood estimator of the parameters of a cointegrating vector error correction model (VECM) are employed to test the stationary properties of the time series and to examine the long-run relationship between the variables, respectively. The results derived from the analysis confirm the existence of long-run relationship between the accident-related indices and macroeconomic indicators. The long-run elasticity values imply the signs and magnitude of impact of the accident indices on macroeconomic indicators. JEL: R41, H510, I310, I32

PASAR MODAL REGIONAL DALAM MASA KRISIS FINANSIAL 1997 DAN 2007: KAJIAN TERHADAP INTERDEPENDENSI BURSA EFEK ASIA TENGGARA

The devastating effect of the two world finansial crises had widely influenced not only on developed capital markets but also emerging ones, including the ASEAN regional markets. The crises have been commonly believed to have significant impact on the changing behaviour of the regional indices movements. This study investigates how the crises have affected the interrelation of stock indices’ movements amongst the five South East Asian countries. The multivariate time series analysis frameworks applied on series of the two sub-sample periods reveals the existing of a cointegrating relationship among the stock markets during the 1997 finansial crisis, but none of cointegrating vector to be found on the series of the 2007 crisis. The short run dynamic analyses conclude that the short run interrelation among the regional indices seems to be more intense during the 2007 finansial crisis period. For the latest period of crisis, the number of significant causal linkages between two variables on the series was greater than the other period. The analyses also show that the explanatory power of an endogenous variable to another in the system increased during the latest crisis, implying that the contagious effect of the crisis had increased the short run interdependence of the regional stock markets.

The Price Transmission in European Stock Markets

We investigate the dynamic price relationships among ten major stock indexes in Europe before, during and after the recent financial crisis. Using an error-correction model we find that the stock markets are cointegrated with three cointegrating vectors before the crisis and that the markets are cointegrated with only one cointegrating vector during and after the crisis. We further apply directed acyclic graph (DAG) analysis on the contemporaneous correlations innovation matrix to explore the instantaneous transmission pattern. The results show that France and Spain appear to share leadership roles before the crisis while leadership role is less obvious during and after the crisis. We also find a decreasing number of instantaneous casual relationships between the markets after the crisis, indicating that the markets are becoming more independent.

PASAR MODAL REGIONAL DALAM MASA KRISIS FINANSIAL 1997 DAN 2007: KAJIAN TERHADAP INTERDEPENDENSI BURSA EFEK ASIA TENGGARA

The devastating effect of the two world finansial crises had widely influenced not only on developed capital markets but also emerging ones, including the ASEAN regional markets. The crises have been commonly believed to have significant impact on the changing behaviour of the regional indices movements. This study investigates how the crises have affected the interrelation of stock indices’ movements amongst the five South East Asian countries. The multivariate time series analysis frameworks applied on series of the two sub-sample periods reveals the existing of a cointegrating relationship among the stock markets during the 1997 finansial crisis, but none of cointegrating vector to be found on the series of the 2007 crisis. The short run dynamic analyses conclude that the short run interrelation among the regional indices seems to be more intense during the 2007 finansial crisis period. For the latest period of crisis, the number of significant causal linkages between two variables on the series was greater than the other period. The analyses also show that the explanatory power of an endogenous variable to another in the system increased during the latest crisis, implying that the contagious effect of the crisis had increased the short run interdependence of the regional stock markets.