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We compare methods to measure comovement in business cycle data using multi-level dynamic factor models. To do so, we employ a Monte Carlo procedure to evaluate model performance for different specifications of factor models across three different estimation procedures. We consider three general factor model specifications used in applied work. The first is a single-factor model, the second a two-level factor model, and the third a three-level factor model. Our estimation procedures are the Bayesian approach of Otrok and Whiteman (1998), the Bayesian state-space approach of Kim and Nelson (1998) and a frequentist principal components approach. The latter serves as a benchmark to measure any potential gains from the more computationally intensive Bayesian procedures. We then apply the three methods to a novel new dataset on house prices in advanced and emerging markets from Cesa-Bianchi, Cespedes, and Rebucci (2015) and interpret the empirical results in light of the Monte Carlo results.

The purpose of this paper is to examine the effects of several structural shocks in oil prices on the Vietnamese economy and answer three key research questions: Is there a relationship between oil price shocks and macroeconomic indicators in Vietnam? How do different types of oil price impulses affect Vietnamese inflation and economic performance? To what extent do structural shocks in oil prices explain variations in Vietnam’s macroeconomic indicators?

Lower triangular Cholesky decomposition is performed on a short-term impact matrix in a two-block structural vector autoregressive model. The data set is defined monthly, from January 2000 to December 2021. The contributions of structural shocks in oil prices to the domestic variances are analysed using variance decomposition methods. In this study, both forecast error variance decomposition and historical decomposition are used.

The consequences of oil price fluctuations on Vietnamese output and inflation depend on different sources of oil price shocks. In comparison, oil supply shocks have an insignificant effect on both domestic industrial output and consumer price index inflation; however, positive shocks in aggregate and precautionary oil demands increase these domestic indicators substantially and sustainably. An analysis of variance decompositions reveals that supply-side oil shocks have very limited explanatory power for variations in domestic variables. Nevertheless, the contributions of unanticipated demand-side booms to domestic variations in the past and projected forecasts are considerable.

The findings from this research uncover potential risks for Vietnam’s economic prospects if the consequences of oil price shocks are not managed effectively.

Given the lack of economic sensitivity to supply-side oil shocks and the strong response to shifts in oil demands, greater pressure on the domestic economy is likely when Vietnam increases its dependence on oil imports.

The purpose of this paper is to investigate the influence of the real interest rates, inflation and risk premium on the time deposit rates of banks in the dual banking system in Malaysia.

The data consists of 1-, 6- and 12-month average time deposit rates of conventional and Islamic banks over the period of January 2000 to June 2017. The cointegration methodologies are used to explore links between the time deposit rates, real rates, inflation and risk premium. The causality tests to test causality linkages between pairs of variables are also applied. The generalised forecast error variance decomposition based on the error correction model is conducted to analyse the impact of variables variation on the deposit rates.

The results show the presence of two cointegration vectors in the deposit rates, real rates, inflation and risk premium, for both conventional and Islamic bank rates. Causality tests reveal that deposit rates are caused by inflation and risk premium in a one-way causality. The results of variance decomposition highlight the importance of inflation and risk premium in explaining the variations in the bank deposit rates. For the conventional bank, inflation shocks play the most important role in explaining the movements of the deposit rates. In Islamic banks, the major determinant’s largest influence is the risk premium. Between the two bank rates, Islamic bank rates receive more influence from the explanatory variables in the long-run compared to conventional bank rates. The real rates have no noticeable effect on the variance of time deposit rates for both banks.

This study presents new evidence on the relationship between time deposit rates and the three explanatory variables, which are the real interest rates, inflation and risk premium, for both conventional and Islamic banks in Malaysia. The dual banking system allows exploring the similarities and differences between conventional and Islamic banks in Malaysia in terms of the linkages between the variables.

The purpose of this paper is to provide empirical evidence for individual educational investment decisions and to investigate the relative importance of two factors, the type of education (vocational vs academic) and subject area (e.g. commercial or health), in determining variance in earnings.

Using a sample of 1,200 individuals based on the 2011 Swiss Adult Education Survey, Mincer-type earnings equations are estimated. The variance in earnings is decomposed with respect to the two factors mentioned above, which allows to quantify the relative contributions of type of education and subject area to variance in earnings.

The results of the variance decomposition show that subject area explains nearly twice the variance in earnings compared with that explained by type of education.

As results show that earnings variance – and thereby risk – relate more to subject area than to type of education, this study suggests that for individuals caring about the risk of their educational decision the selection of a specific subject area is more relevant than the choice between vocational and academic tracks; in addition, educational policies as part of HRM policies should devote as much attention to the choice of subject areas as to vocational or academic education. This is especially important for companies or countries planning to introduce or to extend vocational education as part of their human resources strategies.

This study is the first to show whether earnings vary more by type of education or by subject area.

The purpose of this paper is to examine the role wage dispersion across establishments has played in recent increases in total wage inequality in Germany and compares it to inequality changes at the individual level. It is queried whether the contribution of establishment heterogeneity to the rise of wage inequality stems from changes of institutional settings or from structures such as establishment size and the composition of the workforce.

Applying regression-based decompositions of variance to German linked employer-employee panel data for the years 2000-2010 it is analysed to what extent changes associated to firm structures contribute to the rise of total wage inequality.

Results show that the rise in wage inequality in Germany to a great extent is associated to rising wage variance across establishments, implying that establishment specific wage premiums have grown. By further decomposing across firm components of wage inequality, it is found that changes in across establishment wage inequality related to collective bargaining, worker co-determination and internal labour markets together account for about 3 per cent of the rise in total inequality. Inequality changes related to establishments’ skill and occupational composition account for about 11 per cent and establishment size alone accounts for about 18 per cent of the rise in total inequality.

The main contribution is to quantify the relation of specific establishment characteristics to the rise in total wage inequality over time. Conclusions are drawn about the importance of mechanisms of rent sharing at the firm level in comparison to the determination of wages by individual qualification.

This paper aims to explore the impact of the coronavirus on the volatility spillovers of 10 selected developed markets hit by this pandemic (e.g. the USA, Canada, Korea, Japan, the UK, Germany, Italy, Spain, France and China).

The database consists of daily data from January 1, 2020, to December 31, 2022. The data used are the precise daily closing prices of various indices of selected markets gathered from the DataStream and Investing.com databases. The authors use the VAR model to study the transmission of volatility between stock markets and analyze the dynamic links between them. Then, the Granger causality test is used to study the volatility movements and determine which of these markets is likely to influence the others. Then, impulse response functions are used to understand the reactions of the studied markets following shocks in the two most important markets, namely, the American and Chinese markets. Finally, forecast errors variance decomposition is used to measure the dynamic interactions that characterize the relationships between the studied markets.

Empirical results reveal instability in the returns of various indexes and the existence of causal relationships between standardized volatility of markets. The reactions of some markets following a shock in American and Chinese markets differ among markets. The empirical results also show that forecast errors variance of some markets begin coming from their own innovations during first periods. These shares decrease then in favor of other markets interventions.

The findings have significant practical implications for governments around the world as well as for financial investors. The successful practice of China’s pandemic prevention and control efforts may inspire governments to determine how to overcome panic and strengthen confidence in victory. Policymakers can use the insights from our study to design more effective economic policies and regulations to mitigate the negative impact of future pandemics on the financial system. Regulators can use these results to identify areas of weakness in the financial system and take proactive measures to address them. Financial investors may use the outcomes of our result to better understand the impact of global pandemics on financial markets. They may know which markets are the most active, which ones are causing considerable effects on the others and which ones show resilience and an anti-risk capacity. This may help them to make appropriate decisions about their investments.

It has become imperative to estimate the impact of this pandemic on the behavior of financial markets to prevent the deterioration and dysfunction of the global financial system. The findings have important implications for financial investors and governments who should know which markets are the most shaken, which cause remarkable effects on others and which show resilience and anti-risk capacity. Countries could follow China in some measures taken to moderate the negative effects of this epidemic on national economies.

This paper aims to study the co-integration among the stock markets of BRIC nations of Brazil, Russia, Indian and China to analyze if the series move apart or they move together in the long term. and to examine the implied volatility transmission between the Indian implied volatility index and three international indices and vice-versa by using synchronized daily data by using techniques such as generalized impulse response functions and variance decompositions. More specifically, the authors investigate how shock to one volatility index affects another volatility index and what is the magnitude and sign of affect and how long does the effect persist?

Unit root tests are conducted to determine the order of integration for each index. The cointegration analysis is used to evaluate the co-movement of a long-term equilibrium relationship among the four stock market indices. Variance decomposition test helps to explain that how much movement in the dependent variable is explained due to its own shock vis-a-vis to the shock of other variables under the study. Impulse response function is used to find out the impact of the standard deviation of shock given to one variable on the impact on the other variable.

There exists one long-run cointegrating relationship between the four stock markets under study. The coefficient of VECM is −0.00031 which is negative and highly significant at 1 per cent. This confirms the existence of a stable long-run causal relationship between the variables. Variance decomposition shows that indices of Brazil, China and Russia can explain on average 4, 0.5 and 5 per cent, respectively, of the forecast error variance of Indian index. On the other hand, Indian market can explain on an average 6.7, 5 and 3 per cent of the forecast error of Brazilian, Chinese and Russian markets, respectively.

The research paper is an original work of the author.

This study investigates the long-run relationship between workers' remittances and human capital formation in Sri Lanka by using the macro-level time series data during the period of 1975–2020.

In this study, the augmented Dickey–Fuller (ADF) and Philips–Perron (PP) unit root tests, the autoregressive distributed lag (ARDL) bounds cointegration technique, the Granger causality test, the forecast error variance decomposition technique and impulse response function analysis were employed as the analytical techniques.

In accordance with the results of unit root tests, the variables used in this study are mixed order. Results of cointegration confirm that workers' remittances in Sri Lanka have both long-run and short-run beneficial relationship with human capital formation. The Granger causality test results indicate that there is a two-way causal relationship between workers' remittances and human capital formation. The results of forecast error variance decomposition expose that innovation of workers' remittances contributes to the forecast error variance in human capital in bell shape. Further, the empirical evidence of impulse response function analysis reveals that a positive standard deviation shock to workers' remittances has an immediate significant positive impact on human capital formation in Sri Lanka for a period of up to ten years.

This research provides insights into the workers' remittances in human capital formation in Sri Lanka. The findings of this study provides evidence that workers' remittances help to produce human capital formation.

By using the ARDL Bounds cointegration and other techniques in Sri Lanka, this study fills an important gap in academic literature.

This paper examines the impact of macroeconomic and risk factors on the profitability and volatility of professional momentum portfolios for the US, the UK, Japan and Germany, for the period 1998–2018. Many of the factors employed, such as energy price changes and economic policy uncertainty, have been largely neglected in the relevant literature.

Regression analysis, VECTOR AUTOREGRESSION (VAR), Panel-VAR, Variance Decomposition Analysis

The results indicate that, since the financial crises in the US and the EU, energy prices and economic-policy uncertainty have become important return determinants, along with market-related uncertainty that seems to have a stable impact over time, especially for the U.S. and U.K. portfolios.

Economic policy uncertainty significantly affects contemporaneous momentum returns in the US, UK and Japan, mainly between 2007 and 2018, while market-related uncertainty affects all markets during all subperiods. In addition, the variance of market-related uncertainty (VIX) explains a large percentage of the variance in the momentum returns for the US, UK and Germany.

The main implication of the findings for portfolio managers is that a manager may increase (decrease) exposure to the momentum factor during optimistic (pessimistic) periods and during periods of rising energy prices (high economic policy and market-related uncertainty).

The paper examines the impact of factors, such as energy prices and economic policy uncertainty, which have been largely neglected in the relevant literature on the possible drivers of the momentum strategies. It employs professional portfolios that are often used in practice as benchmark indexes.

The purpose of this paper is to examine the causal relationships between stock prices and macroeconomic variables in Sri Lanka, in order to examine the validity of the semi‐strong form of the efficient market hypothesis.

The paper adopts unit roots and cointegration, error‐correction modelling, variance decomposition analysis, and impulse responses analysis to examine the causal relationship between six macroeconomic variables.

The results indicate that there are both short and long‐run causal relationships between stock prices and macroeconomic variables. These findings refute the validity of the semi‐strong version of the efficient market hypothesis for the Sri Lankan share market and have implications for investors, both domestic and international.

The paper addresses several methodological weaknesses in relation to unit root and cointegration tests which previous studies in the area of the paper have overlooked. Further, it uses more variables than those used in a previous study using Sri Lankan data.