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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.

One of the highly debatable issues in the arena of international economics in recent years is whether a country should go for full capital account convertibility. In terms of the timing and process of capital account liberalization, India and China have been remarkably similar. Both started with a more or less closed capital account in the 1970s and the 1980s, in the context of a heavily state-influenced, planned economy. And in both countries, the first wave of liberalization came in the early 1990s and thus, the journey began. The objective of this chapter is to provide a critical analysis of both India and China's approach to the capital account liberalization program in the backdrop of the recent financial crises and to give an account of the theoretical issues that have arisen in international discussions on CAC and India's standpoint on this issue in particular. Second, how far is the capital account liberalization justified in the context of the recent episodes of financial crises that India and China have witnessed? Using a macroempiric model, this chapter tries to answer whether every member country in the IMF should hurriedly go for CAC or not. In addition, empirically through FMOLS, the authors pool in the “Rupee Convertibility” and “Renminbi Internationalization” along with exchange rate variation and its implications for India's and China's BoP situation (in terms of the export–import position and FDI flows) based on data from 1992 to 2017. ^{1 , 2}

For the past decades, issues concerning the impact of economic integration on financial integration, especially exchange rate integration, has been criticized among several regions such as ASEAN. This chapter intends to: (i) test for the exchange rate integration among the ASEAN-5, including Indonesia, Philippines, Malaysia, Singapore, and Thailand, using panel data techniques; and (ii) determine the impact of economic integration on the level of exchange rate integration among the ASEAN-5 countries. The purchasing power parity (PPP) is tested using panel unit root tests on monthly data. The results confirm the PPP among the ASEAN-5 countries due to lower transaction costs from ASEAN agreements. The chapter applies Multivariate GARCH (M-GARCH) models using daily data to determine the level of exchange rate integration among the ASEAN-3, including Malaysia, Singapore, and Thailand. The results of panel cointegration tests using quarterly data of economic integration and exchange rate integration confirm the impact of international trade openness on exchange rate integration. With free trade agreements leading to lower trade barriers, lower transaction costs, and low transportation costs, the economic integration among ASEAN countries practically leads to a higher degree of exchange rate integration. The findings imply that trade liberalization has the strongest effect on the real exchange rate. As such, regulators of ASEAN countries should pay more attention to the exchange rate policies of each other because of the interdependence of their exchange rates.

The search for more effective policies, choice of optimal implementation strategies for achieving defined policy targets (e.g., cost-containment, improved access, and quality healthcare outcomes), and selection among the metrics relevant for assessing health system policy change performance simultaneously pose continuing healthcare sector challenges for many countries of the world. Meanwhile, research on the core drivers of healthcare costs across the health systems of the many countries continues to gain increased momentum as these countries learn among themselves. Consequently, cross-country comparison studies largely focus their interests on the relationship among health expenditures (HCE), GDP, aging demographics, and technology. Using more recent 1980–2014 annual data panel on 34 OECD countries and the panel ARDL (Autoregressive Distributed Lag) framework, this study investigates the long- and short-run relationships among aggregate healthcare expenditure, income (GDP per capita or per capita GDP^_HCE), age dependency ratio, and “international co-operation patents” (for capturing the technology effects). Results from the panel ARDL approach and Granger causality tests suggest a long-run relationship among healthcare expenditure and the three major determinants. Findings from the Westerlund test with bootstrapping further corroborate the existence of a long-run relationship among healthcare expenditure and the three core determinants. Interestingly, GDP less health expenditure (GDP^_HCE) is the only short-run driver of HCE. The income elasticity estimates, falling in the 1.16–1.46 range, suggest that the behavior of aggregate healthcare in the 34 OECD countries tends toward those for luxury goods. Finally, through cross-country technology spillover effects, these OECD countries benefit significantly from international investments through technology cooperations resulting in jointly owned patents.

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.

Introduction: Financial development has a direct impact on the housing market by facilitating access to credit. The increase in housing loans resulting from the relaxation of the credit constraint causes an increase in housing demand and house prices. Purpose: This study aims to examine the relationship between financial development and house prices in Turkey, using the variables: the domestic credit to the private sector and total housing and consumer credits. Methodology: To determine any long-run relationship between financial development and house prices, the autoregressive distributed lag methods are used, covering the selected variables such as real GDP, inflation, mortgage interest rate, and stock price from 2010Q1 to 2020Q2. Findings: The study’s findings show that both variables representing financial development have a statistically significant and substantial positive effect on house prices. Besides, the selected macroeconomic variables have the theoretically expected impact on house prices.

Using the Environmental Kuznets Curve (EKC) hypothesis as a theoretical framework and applying Estimated Generalised Least Square (EGLS) approach, this chapter examines the impact of energy consumption, economic growth, industrialisation and corruption on carbon dioxide emissions as well as finds out the causal relationship among them using panel data of 10 Asian economies over the period 1980–2019. Our empirical findings from EGLS model suggest that there exists an ongoing rising relationship between CO₂ emissions and economic growth both in the short-run and long-run which is opposing to what is claimed by the EKC hypothesis. Moreover, per capita CO₂ emissions rise positively with respect to increase in energy consumption, urbanisation, gradual industrialisation and growth in urban population in the long-run. Moreover, countries with adoption of more corruptive practices are found to have causing more environmental degradation through excessive emission of carbon dioxide in the long-run. The study also indicates the existence of unidirectional causalities running from carbon dioxide emission to energy consumption, from industrialisation and urban population growth to per capita CO₂ emissions, from industrialisation to GDP growth per capita and bidirectional causality between financial development and economic growth via GDP growth per capita. Therefore, these unidirectional causalities entail that CO₂ emission reduction or abatement measures can be applied without having any unpleasant effect on the real industrialisation, energy consumption and urbanisation in selected Asian countries.

This chapter investigates the social determinants (urbanisation, population, literacy and corruption) of greenhouse gas (GHG) emissions in the top 100 developed and developing emitting countries. The data were collected from central repositories for the different variables explored for the period 2012–2020 in a cross-country analysis. Fixed effects ordinary least squares (OLS) regression was used to analyse the data. The results for all top 100 countries and developing countries show that urbanisation and corruption are significantly positive and negative determinants of GHG emissions, respectively. In addition, literacy is a significant positive determinant of GHG emissions in developing countries but not in the top 100 and developed countries. Population is not significant in the top 100 developed and developing countries. The results for the control variables suggest that primary energy consumption is a positive significant determinant of GHG emissions in the top 100 developed and developing countries. However, gross domestic product (GDP) is not a significant determinant of GHG emissions. The findings have important policy implications.

One of the most significant changes in monetary economics at the beginning of the twenty-first century has been the virtual disappearance of what was once a dominant focus, the role of money in monetary policy, and parallelly, the disappearance of the liquidity preference-money supply (LM) curve. Economists used to consider monetary policy with the help of the LM curve as part of the analytical framework which captures the demand for money. However, the workhorse model of modern monetary theory and policy, the New Keynesian Dynamic Stochastic General Equilibrium (DSGE) framework, only comprises the dynamic investment-savings (IS) curve, the New Keynesian (NK) Phillips curve, and a monetary policy rule. The monetary policy rule is generally known as the Taylor rule. It relates the nominal interest rate to the output-gaps and inflation-gaps, but typically not to either the quantity or the growth rate of money. This change in the modern monetary model reflects how the central banks make monetary policy now. This study provides a detailed discussion on the role of money in monetary policy formulation in the context of the NK and the New Monetarist perspectives. The pros and cons of abandonment of money or the LM curve from monetary policy models have been discussed in detail.