Narrow Results

This paper examines the causal relationship between central bank intervention and exchange rate returns in India. Using monthly data from December 1997 to December 2011, the empirical results derived from the CCF approach of Cheung and Ng [Journal of Econometrics72 (1996) 33–48] suggest that there is causality-in-variance from exchange rate returns to central bank intervention, but not vice versa. These findings are robust in the sense that they hold in cases where the returns were measured from either the spot rate or the forward rate. Therefore, we conclude that the Indian central bank has intervened in the foreign exchange market to respond to exchange rate volatility, although the volatility has not been influenced by central bank intervention in the form of net purchases of foreign currency in the market.

This paper explores the effectiveness in which the Central Bank of the Republic of China (Taiwan) artificially devalues the New Taiwan Dollar relative to the US Dollar via the major foreign exchange brokered firm in Taiwan. The empirical results support that Taiwan’s central bank targets to step into the major market to influence the exchange rate at some specific intervals. However, the effectiveness of intervention in the major brokered company is short run and might reverse overnight. Moreover, intervention increases the returns and spreads of the two markets for a few minutes. Finally, the effectiveness of moral suasion is insignificant, depending on the timing of interventions and the response of market participants to those interventions.

This paper examines big data analytics implications on the central banking financial system’s technological progress. A digital technological progress framework and model is established to analyze the economy’s aggregate supply via covering the monetary policy, big data analytics, pollutants emissions as independent variables and the economy’s aggregate demand as a moderating variable in a modified extensive growth theory framework and model to compute the productivity indicators and the total factor productivity (TFP) as the central banking technological progress that combined the mentioned variables qualities contribution. Besides, data analytics positive and negative externalities that include data analytics shortcomings as unpriced undesirable output in the form of cybersecurity and pollutants’ emissions among other proxies are internalized in the framework and the model to integrate the digital technology innovation with digital technology shortcomings and climate change. This revised extensive theory framework and model is a remarkable technique comprehensive of the technological progress matters and sustainable economic development and is considered one of the most important sustainable development and long-run economic growth proportions in the central banking financial system functions to manage the economy’s aggregate supply and demand that unnoticed by previous studies.

This paper attempts to distinguish the role of banking sector credit to enterprise and household in economic growth of Pakistan for the period from 1982 to 2017. Using Autoregressive Distributed Lag (ARDL) bound technique to cointegration, our results confirm that enterprise credit has a positive and significant impact on the economic growth of Pakistan for the sample period. In contrast, the other component of private credit, i.e., household credit is not a positive driver of economic growth. CUSUM test finds that the parameters of the model with enterprise and household credit are stable. It is recommended therefore that the central bank should modify the credit policy for household sector and support enterprise credit in the context to achieve sustainable economic growth in Pakistan.

The following sections are included:

• Introduction
• Reserve Requirements — An Overview
• Research Design and Methodology
• Robust Regression Results
• Conclusion
• Notes
• References
• Appendix A
• Appendix B
• Appendix C
• Appendix D
• Appendix E