Examining the association between stock return and seasonally adjusted trade in India

This paper aims to examine the association between Indian stock market return and seasonally adjusted trade for Indian Banking sector shares. The objective of the study is to measure the association between stock return and seasonally adjusted trade in the Indian stock market and recommend strategies. Due to the Covid 19 outbreak banking sector was highly affected, the Government of India also announced a moratorium on all categories of loans, banking business majorly depending on the deposit and loan creation, so the Government decision threaten the banking sector. Many private sector banks terminated temporary staff because of cut cost policies. We divided the banking sector into three segments. Namely, Public, Private and Small Finance Banks. Utilizing daily data from February 2020 to July 2020, consisting of 2196 in numbers, we ran a panel Vector Autoregression model to analyze the association. It was found that the return of stocks is influencing the volume of trade during this period. Also, while measuring the short-run causality, it is found that the return of banking stocks specifically granger causes the volume of trade. The suggestions of the study lie in providing importance to framing policies on improving the financial health of the economy through different fiscal policies. Strategic policies are required to face post-Covid situations. The turnaround strategies to combat the effects of the pandemic are characterized by the availability of the sustainable resources of the particular sector in consideration.

Impact of tourism development on inclusive growth: A panel vector autoregression analysis for African economies

The persistent debate among policy makers and academics around combating the high rates of poverty and income inequality can be further illuminated by understanding how tourism contributes to inclusive growth, especially in developing economies. Tourism sector can be regarded as one of the key contributors to inclusive growth and where it has the capacity to generate prospects for productive employment. The goal of this article is thus to investigate the link between inclusive growth and tourism in the African context. To do this, we utilized a recent panel vector autoregression (pVAR) and data for 45 African countries spanning the period 1995 to 2019. Thus, by the error variance decomposition and impulse response functions, our results showed a weak positive effect of international tourism arrivals and the composite tourism indicator on inclusive growth, while tourism receipts and tourism expenditure insignificantly decreases inclusive growth in the sampled African economies. Our result is further supported by the panel system generalized method of moments (GMM). We provide some policy implications from our findings.

Is Green Credit a Good Tool to Achieve “Double Carbon” Goal? Based on Coupling Coordination Model and PVAR Model

China attaches importance to the combination of credit policy and environmental protection, tries to use credit policy tools to protect ecology and pollution prevention, and prevent environmental credit risk. With the proposal of the goal of “carbon peak and carbon neutralisation” (“double carbon”), green credit is also regarded as an important policy tool to achieve this goal. Firstly, this paper selects the time series data of green credit at the national level from 2013 to 2019 according to the official statistics and evaluates the coupling and coordinated development of credit system and environmental system based on the coupling coordination model. The results show that the two systems show well-coordinated development, but the interaction has annual fluctuations. Secondly, by calculating the provincial carbon emissions and green credit panel data from 2005 to 2019, the dynamic internal mechanism is analysed based on Panel Vector Autoregression (PVAR) model. It is found that green credit has a significant inhibitory effect on carbon emissions. The research results of this paper provide an overall evaluation of the quantity and quality of green credit for China’s banking industry. It also provides reasonable and effective support for green credit as a policy tool to promote realising the “double carbon” goal. In addition, China should maintain the consistency, stability and durability of green credit policy and continue to contribute to the low-carbon transformation of the economy and society.

THE IMPACT OF MACROECONOMIC POLICY ON ECONOMIC GROWTH IN SUB-SAHARA AFRICAN COUNTRIES

The prime purpose of this article was to investigate the monetary and fiscal policy interaction and their impact on economic growth in a panel of 35 sub-Saharan African economies from 1980 to 2018. To achieve this objective, the study employs a Panel Vector Autoregression (PVAR) estimation technique. Using a PVAR approach, we show that an expansionary fiscal policy through tax revenue and an unexpected expansionary monetary policy via broad money supply have a positive effect on gross national income, whereas an expansionary fiscal policy through the government spending have a contractionary impact on gross national income. We also find that an unexpected expansionary monetary policy via real exchange rate has no effect on gross national income. Finally, we show evidence that there is a negative and significant relationship between fiscal policy and monetary policy and thus supporting the need of policy coordination between fiscal and monetary policies. Therefore, to have continuous and sustainable economic growth, the coordination of monetary and fiscal policies is vital, and the lack of this coordination leads to a sharp downturn of overall economic performance, even can hurt the economy The empirical results also show that the variation in gross national income is more explained by fiscal policy variables than monetary policy variables which show fiscal policy is more effective than monetary policy in influencing gross national income.

Assessing the Impact of the Digital Economy on Green Total Factor Energy Efficiency in the Post-COVID-19 Era

Digital transformation in the energy sector is an essential tool for promoting the construction of a clean energy system in the post-COVID-19 era. Under the background of digital China strategy and sustainable energy transformation in the post-COVID-19 era, it is meaningful to investigate the relationship between the digital economy and green total factor energy efficiency (GTFEE) to better drive the development of the digital economy and improve GTFEE. For this purpose, this study estimates deeply the impact of the digital economy on GTFEE by applying ordinary least squares (OLS), panel vector autoregression (PVAR), panel threshold, and mediation effect models based on panel data of 30 Chinese provinces from 2006 to 2018. The statistical results indicate that digital economy is conducive to improving GTFEE. Digital economy can significantly contribute to GTFEE by improving economic growth level, urbanization level, R&D investment, and human capital. The most interesting finding was that there is also a non-linear relationship between digital economy and GTFEE. The effect of digital economy on GTFEE is shown to be first promoted and then inhibited as digital economy level continues to increase. Further, the positive impact of the digital economy on GTFEE is strengthened with increasing levels of economic growth, urbanization, R&D input, and human capital. Finally, A positive correlation was found between digital economy and GTFEE in the eastern and central regions, but insignificantly in other regions.

Popularity Brings Better Sales or Vice Versa: Evidence from Instagram and OpenTable

With the popularity of user-generated content (UGC), an increasing number of studies have investigated its impact on business performance. However, prior studies were limited to a single platform and showed the effects of UGC of a platform, for example, customer textual comments or customer numeral ratings, on sales/reservation of the same platform. In practice, users often refer to a UGC, for example, Instagram, and purchase it on other platforms. To incorporate the spillover effect, we considered the restaurant industry because it has active participation across various channels. Using topic modelling, we first identified from Instagram four topics of users’ interest regarding a restaurant, such as location, nightlife, food and celebration. From fixed effects models’ estimation, we found that (a) recommendation and mention of Instagram have positive effects, and (b) comments of location and food also have positive significant fixed effects, but (c) the impact of Instagram volume is curvilinear and positive significant effect the sales. Since the curvilinear effects may come from reverse causality, that is, higher reservation, might bring more customers and comments on social networking service (SNS) (echo verse effect in our paper). Therefore, we further analysed two-way Granger causality and panel vector autoregression to identify the endogeneity, and the results showed the existing Granger causality loop between OpenTable review and Instagram post volumes.

Measuring liquidity in agricultural land markets

PurposeLiquidity is an important aspect of market efficiency. The purpose of this paper is threefold: first, this paper aims to discuss indicators that provide information about liquidity in agricultural land markets. Second, this paper aims to reflect on determinants of market liquidity and analyze the relationship with land prices. Third, this paper aims to conduct an empirical analysis for Germany that illustrates these concepts and allows hypothesis testing.Design/methodology/approachThis study reviews liquidity dimensions and measurement in financial markets and derives indicators applicable to farmland markets. In an empirical analysis, this study exhibits the spatial and temporal variability of land market liquidity in Lower Saxony, a German federal state with the highest agricultural production value. This study uses a rich dataset that includes 72,547 sale transactions of arable land between 1990 and 2018. The research focuses on volume-based (number of transactions, volume and turnover) and time-based (trading frequency and durations) measures. A panel vector autoregression and Granger causality tests are applied to investigate the relation between land turnover and land prices.FindingsThe paper confirms the thinness of farmland markets but also reveals regional and temporal heterogeneity of land market liquidity. This study finds that the relation between market liquidity and prices is ambiguous. This study concludes that a high demand from expanding farms absorbs supply shocks regardless of the current price level in agricultural land markets.Originality/valueEven though the relevance of agricultural land markets’ thinness is widely acknowledged in the literature, this paper is one of the first attempts to measure liquidity in agricultural land markets and to explain its relationship with land prices.

Electricity Consumption in China: The Effects of Financial Development and Trade Openness

As China is facing the double pressure of economic growth as well as energy-saving and reduction of emissions, reducing electricity consumption without affecting economic development is a challenging and critical issue. Based on 31 provincial panel’s data in China from 2004 to 2018, this study empirically analyzes the direction and degree of the impact of financial development and trade openness on electricity consumption using the spatial econometric approach and panel vector autoregression (PVAR) model. The results indicate that China’s electricity consumption presents a significant spatial spill over effect, and the spatial agglomeration of electricity consumption in local regions is mainly HH clusters. A 1% positive change in financial development causes an increase of 0.089% in electricity consumption, but a 1% rise in financial development reduces electricity consumption of neighboring regions by 0.051%. A 1% positive change in trade openness decreases electricity consumption by 0.051%, while the spatial spillover effect of trade openness is not significant. It is also found that financial development has a long-term promoting effect on electricity consumption, while trade openness has a long-term inhibiting effect on electricity consumption.

Analysis of the Financing Structure of China’s Listed New Energy Companies under the Goal of Peak CO2 Emissions and Carbon Neutrality

Under China’s “Dual Carbon” strategic goal, electric energy substitution on the energy consumption side and clean substitution on the energy supply side have become an important path to achieve peak CO2 emissions and carbon neutrality. Adjusting the energy structure and encouraging new energy to replace traditional energy is an important manifestation of China’s energy supply revolution. Therefore, China’s new energy companies have grown rapidly over the past decade. The development and growth of this industry is inseparable from government policy support. The profitability and economy are essential for the new energy industry to support its sustainable development., especially the choice of business models such as operation model and financing structures. Therefore, we build extended panel vector autoregression (PVAR) models with two-step system GMM(SYS-GMM) estimator which introduced predetermined and strictly exogenous variables to explore the dynamic correlation between financing structure and economic performance of China’s new energy public companies. The number of patent approvals and financial leverage are introduced as exogenous control variables. The results show that although the increase in costs caused by financing behavior will have a negative impact on the company’s return on equity in the short term, with the rational investment and utilization of funds, the negative impact will gradually weaken. Listed new energy companies can effectively use financing funds, and the use of different financing tools has different effects on company performance. Although debt financing can help promote the company’s profitability, it is detrimental to its future growth capacity.