Search results

This paper provides a selective survey of the panel macroeconometric techniques that focus on controlling the impact of “unobserved heterogeneity” across individuals and over time to obtain valid inference for “structures” that are common across individuals and over time. We consider issues of (i) estimating vector autoregressive models; (ii) testing of unit root or cointegration; (iii) statistical inference for dynamic simultaneous equations models; (iv) policy evaluation; and (v) aggregation and prediction.

The resistance of the energy sector in recent time has been tried by COVID-19 as the occurrence has added to the dampening down demand for crude oil which has resulted in volatility in prices and dwindling production of crude oil at the global crude oil market. Dwindling demand and price decline can also be perceived as a trend in the electricity sector, the electricity price (ELECTP) and consumption. The consequences of individual policy response by countries in relation to the socio-economic impact of COVID-19 is yet to be known, and recent studies conducted in the continent are yet to document the impact of the pandemic on the oil-producing African countries. It is in the light of this that this study determined the effect of socio-economic shocks activated through the COVID-19 pandemic on the energy sector performance and economic development of Africa. Monthly data were sourced from the United States Energy Information Administration, COVID-19 geographic distribution worldwide, World Development Indicator and Trading Economics from 2019 (m12) to 2020 (m10). Seventeen oil-producing African countries were selected across the region based on data availability. The structural panel vector auto regression (SPVAR) analytical technique was used in estimating COVID-19 pandemic and socio-economic shocks on the energy sector performance proxied by oil production (OILP), ELECTP and economic development proxied by gross domestic product per capita (GDPPC) of the countries. Findings revealed that the COVID-19 pandemic transmits a negative shock to OILP and GDPPC while a positive shock is transmitted to ELECTP. The socio-economic variables also transmitted both the positive and negative shocks to OILP, ELECTP and GDPPC. Therefore, the study recommended that policies should be directed towards putting in place a shock-absorbing mechanism so as to cushion the effect of the identified shocks on the performance of the energy sector and the economic development of the countries.

The presence of economic power of BRICS nations could be felt from the late of nineteenth and beginning of twentieth century and during this period inflow of FDI also began to go up and spread across all the sectors. FDI has not only looked to capture the huge market of these economies, but while doing so, it has helped these nations in their economics progress. Our main contribution in this paper consists of analyzing both short-run and long-run interactions between status of knowledge and FDI in the form of inflow of FDI and proportion of GDP used for R&D activities accounting for possible development of knowledge in BRICS nations. For this purpose, our work is based on a sample of these five nations during the period 2006–2017. By the help of panel data analysis and having performed all the necessary tests, we have introduced both dynamic OLS and fully modified OLS to get the efficient long-run impact of FDI on knowledge. Our empirical results support long-run and short-run causality running from FDI to knowledge in all BRICS nations. Our policy recommendation includes encouragement of more FDI in development of knowledge-related activities as well as increase in proportion of GDP spent on R&D in BRICS nations.

This chapter provides an overview of topics in nonstationary panels: panel unit root tests, panel cointegration tests, and estimation of panel cointegration models. In addition it surveys recent developments in dynamic panel data models.

In this chapter, we study the asymptotic distributions for ordinary least squares (OLS), fully modified OLS (FMOLS), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FMOLS, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic distribution of the OLS estimator is shown to have a non-zero mean. Monte Carlo results illustrate the sampling behavior of the proposed estimators and show that (1) the OLS estimator has a non-negligible bias in finite samples, (2) the FMOLS estimator does not improve over the OLS estimator in general, and (3) the DOLS outperforms both the OLS and FMOLS estimators.

Advances in Econometrics is a series of research annuals first published in 1982 by JAI Press. In this paper, we present a brief history of the series over its first 30 years. We describe key events in the history of the volume, and give information about the key contributors: editors, editorial board members, Advances in Econometrics Fellows, and authors who have contributed to the great success of the series.

This chapter uses fully modified OLS principles to develop new methods for estimating and testing hypotheses for cointegrating vectors in dynamic panels in a manner that is consistent with the degree of cross sectional heterogeneity that has been permitted in recent panel unit root and panel cointegration studies. The asymptotic properties of various estimators are compared based on pooling along the ‘within’ and ‘between’ dimensions of the panel. By using Monte Carlo simulations to study the small sample properties, the group mean estimator is shown to behave well even in relatively small samples under a variety of scenarios.

This chapter investigates attention theory by examining retail investors' true intention to purchase. Attention theory indicates that investors, and especially retail investors, typically invest in stocks about which they are aware. Previous studies test attention theory by analyzing stock price behavior or trading volume. However, stock prices and trading volume are primarily driven by institutional investors rather than retail investors. We examine investor attention using initial public offering (IPO) subscriptions in Taiwan because only retail investors are allowed to subscribe to Taiwanese IPOs. We use media coverage as a measure of passive retail investor attention and Google search volume as a measure of active retail investor attention. Our results reveal that active attention has a more profound relationship with retail investor IPO subscriptions than passive attention does. Additionally, information about the value of IPOs taken from trading prices in the pre-IPO market mitigates the effects of attention theory.

This chapter examines the relationship between directors and officers (D&O) liability insurance and stock-price synchronicity by testing competing corporate governance-related monitoring and moral hazard-related agency conflict hypotheses. Testing a sample of stocks listed on the Taiwan Stock Exchange and the Taipei Exchange for 2008–2020, the empirical results of this study indicate that D&O insurance in Taiwan is negatively correlated to stock-price synchronicity. This negative relation is robust to a battery of tests, including those of fixed-effects regression models, alternative sample periods, alternative synchronicity measures, and alternative insurance measures. Further evidence indicates that this negative relationship is more pronounced among firms with greater agency problems, especially during periods of high market uncertainty. Overall, these findings support the corporate governance-related monitoring hypothesis, which posits that firms with greater D&O insurance are likelier to be characterized by better governance structures and information transparency. Additionally, their stock prices are more likely to reflect firm-specific information in a timely and precise manner, and they are more likely to have lower synchronicity with the industry and market.