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The purpose of the paper is to address money demand instability and investigate the impact of economic uncertainty, stock market uncertainty and monetary uncertainty on money demand in India over the period 2003Q1–2019Q4.

The study checks the stationarity of the variables through standard unit root tests. Based on the mixed order of variables' integration, the authors adopt the autoregressive distributed lag (ARDL) model to confirm the cointegration and check the stability of the money demand function (MDF).

The findings confirm the presence of cointegration and reveal a well-specified MDF, which exhibits stable parameters. Besides the conventional variables, all forms of uncertainties emerge as the essential long-term determinants of money demand. Long-run findings show that people demand more money to avoid the future financial crunch amid high economic, monetary and stock market uncertainties.

The paper recommends, based on the findings, incorporating the monetary aggregates in the monetary policy framework as one of the essential information variables to control the fluctuation in the price level under the current flexible inflation targeting (FIT) regime.

The findings also add to the knowledge of economic agents in terms of the overall response of individuals to changes in different forms of uncertainties, thereby helping to formulate their portfolios more diligently.

The current work is the first of its kind in the Indian context. The incorporation of uncertainty measures in the MDF adds to the existing knowledge on money demand.

The purpose of this paper is investigate the dynamic linkages among industrial energy use, industrial value added, financial development (FD) and trade openness, in case of India. The study covers the annual frequency data on both aggregate and disaggregate variables for the period 1971–2016.

The autoregressive distributed lag bounds testing approach is applied to examine the long-run relation among variables under consideration. Also, Johansen and Juselius (1990) and vector error-correction mechanism results confirm the result of cointegration. Furthermore, non-linear relationship in the model is also tested.

It has been found that there exists long-run relationship among variables. Long-run estimates show that increasing FD leads to more energy uses. Hence, FD should be directed in such a way that it incentivises firms to invest in energy-efficient technology. Furthermore, it is also found that study supports the evidence of conservative hypothesis, which supports that the energy conservation policy should be adopted in the industrial sector. Energy efficiency programme needs to be designed very carefully to achieve a higher level of energy efficiency. This leads to a sustainable growth and low carbon emission.

This paper examines the recent trend in Indian industrial energy consumption and does a comprehensive analysis using a robust econometric method. We have developed a lucid model to examine the deriving factors of industrial energy consumption.

The present study empirically examines the impact of coronavirus disease 2019 (COVID-19) and policy uncertainty on stock prices in India during the COVID-19 pandemic.

To this end, the authors use the daily data by applying the autoregressive distributed lag (ARDL) model, which tests the short- and long-run relationship between stock price and its covariates.

The study finds that increased uncertainty has adverse short- and long-run effects on stock prices, while the vaccine index has favorable effects on stock market recovery.

From investors' perspectives, volatility in the Indian stock market has negative repercussions. Therefore, to protect investors' sentiments, policymakers should be concerned about the uncertainty induced by the COVID-19 pandemic and similar other uncertainty prevailing in the financial markets.

This study used the news-based COVID-19 index and vaccine index to measure recent pandemic-induced uncertainty. The result carries some policy implications for an emerging economy like India.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0244

This paper aims to understand the effect of a change in Economic Policy Uncertainty (EPU) of India and the USA on investors' sentiment in the Indian context, consisting of Sensex returns and volatility index (Vix).

The authors employ bounds testing approach to cointegration to capture the short-and long-run effects of EPU on investors' sentiment, along with impulse response functions and variance decompositions to check the effect of a shock on Sensex and Vix.

The study concludes the existence of a cointegrating relationship for both models, that is, Vix and Sensex. In the long-run, changes in EPU_India affect Vix and Sensex positively and negatively, respectively. On the other hand, EPU_USA affects Vix and Sensex positively. Furthermore, Gregory and Hansen (1996) cointegration with endogenous structural break reveals a long-run cointegrating relationship for both models.

The effect of EPUs on investors' sentiment reveals that when there is an uncertain event that adversely affects the stock prices, investors should not make haste to take a decision as the impact on stock prices perturbation might be temporary. Therefore, one should persevere for the dip in prices to hit the desired target.

Various studies look at the effect of cross-country EPU on the home country, However, there is no such study in the Indian context. The present study examines the impact of India's EPU on investors' sentiments after controlling the USA's EPU, one of India's largest trading partners and a key determinant of global economic policy.

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.