Latest preprints

Following Ramsey, the existing literature on optimal taxation only compares the pre- and post-tax market equilibriums in order to account for the efficiency losses. However, when the government imposes an ad valorem tax on the consumer, the buyer's price jumps to the pre-tax equilibrium price plus the amount of the tax, and the supply and demand of the taxed commodity then adjust over time to bring about the new post-tax market equilibrium. The existing literature does not take into account the efficiency losses during the adjustment process while computing the optimal ad valorem taxes. This paper shows how the adjustment process influences the optimal ad valorem taxes, minimizing the efficiency losses (output and/or consumption lost) during the dynamic adjustment process as well as at the post-tax market equilibrium. (JEL H20, H21, H22)

Financial Inclusion seems to be the light at the end of the tunnel to achieve the Millennium Development Goals (MDGs) which can eradicate poverty and help people to come out of abject poor conditions. Financial Technology (FinTech) is spreading at a fast pace and being accessed by the masses. Thus, this technological innovation which helps to deliver financial services more conveniently and efficiently can hold the key for financial inclusion and women empowerment through financial inclusion. This study used data from the World Bank’s 2017 Global Findex report and tried to find a relation between FinTech and financial inclusion from 144 countries. A few parameters from the report were taken to measure the financial inclusion variable and some indicators were selected to assess the FinTech reach. The results suggested that there is a strong relationship between the independent variable FinTech and the dependent variable financial inclusion for the whole population and women population alone. The study also found that low-income countries are financially excluded while high-income countries are more inclusive except few exceptions. The study will help to understand the impact of FinTech on the inclusion of the excluded population from the financial system and can act as a solution for reducing poverty and women's empowerment.

Over recent decades, the U.S. auto insurance industry has secured tight control over the auto collision repair (ACR) industry through a use of preferred provider networks of captive ACR shops under contract with individual auto insurers. By exercising control over the ACR industry, auto insurers claim they have instituted a better, safer and more efficient system of auto repair service provision, but the independent ACR shops tell a quite different tale of market power abuse, steering of ACR jobs into insurers’ own direct repair provider (DRP) networks, undue control over reimbursements and damage appraisals, suppression of ACR labor rates, and improper reputational losses due to ‘tortious interference’ with these shops’ customer relations.These independent ACR shops have fought back through litigation and politics, trying to wrest control of their industry back into their own hands to restore a level competitive field of fair rivalry in place of an autocratic control by insurers over repairs, labor rates and revenues. For litigation efforts and regulatory initiatives, some assessment of the allegedly illegal behavior is needed, and there is seldom adequate data available for this purpose. The aim of this paper is to present a method of calculating the losses incurred by an individual independent ACR shop pursuant to an auto insurer’s adverse steering of jobs and its suppression of hourly labor rates against this shop. One of the virtues of this method is that it does not require a great deal of information from the auto insurer, as so often a paucity of data is supplied through discovery.The economic analysis of an auto insurer’s steering of jobs is based on an asserted relation of insurers’ market shares to their revenue shares of a large ACR shop’s insurance-based sales. An assessment of the losses due to labor rate suppression is founded on the use of auto mechanical repair (AMR) labor rates as an economic comparable, applied to both the jobs performed under that auto insurer’s policies and to jobs steered away from this single large ACR shop. This study includes a report on the estimated losses suffered by an actual ACR shop in New York State from 2002 to 2007 and discusses some possible limitations, adjustments and tests of the results so produced. At the end, a brief discussion of further research applications appears.

This research delves into the impact of green finance on carbon emissions in India, emphasizing the optimization of energy consumption. The study initiates by exploring the theoretical framework to comprehend how green finance influences carbon emissions, examining the role of energy consumption in this context. To empirically assess this influence, the paper utilizes the STIRPAT model, a chain multiple mediation effect model, and a panel threshold model, using provincial data from India covering the period 2017 to 2022. The findings consistently demonstrate a significant reduction in carbon emissions attributable to green finance, a conclusion upheld even after considering potential endogeneity. Analysis of regional differences highlights a particularly pronounced inhibitory effect in northern, high-carbon emission, and energy-rich regions. Bootstrap tests at the national level reveal three distinct pathways through which green finance curtails carbon emissions: through green technological innovation, the ecological evolution of the industrial structure, and the synergy between green technological innovation and the ecological evolution of the industrial structure. Notably, in energy-rich regions, green finance significantly mitigates carbon emissions through all three pathways, whereas in energy-poor regions, its impact is predominantly linked to green technological innovation.

To analyze tax revenue from its relationship with the sectoral gross domestic product (GDP) becomes essential. Sectoral GDP plays a role in achieving sectoral tax revenue and, in turn, obtaining tax revenue in total. This paper aims to reveal this relationship using empirical evidence. Using a dataset from 34 provinces in Indonesia, the researchers found that industrial, mining, accommodation, and financial sectors positively correlated with tax revenue. On the other hand, agriculture, transportation, and communication correlated negatively with tax revenue. These results have a meaningful implication for the government, particularly for the Directorate General of Taxes (DGT). DGT may apply this result to predict and to establish strategy to boost tax revenue based on the sectoral GDP.

The main objective of the study was to assess the factors affecting the social outreach of microfinance institutions in Ethiopia. The outreach of microfinance was measured in terms of the number of clients served as the breadth of outreach and the socio-economic level of the clients as the depth of outreach. The study was conducted using secondary data collected from the Association of Ethiopian Microfinance Institutions for the period 2007-2020, which was published in its annual bulletin. A sample of 14 microfinance institutions was selected based on the consistency of their financial and performance reports to the association since 2007. The study was based on an explanatory research design. A balanced panel data set was analysed using the random effect panel data regression model. The study found that borrowers per loan officer, cost per borrower, deposit to loan ratio, gross loan to asset ratio, operating expense to loan portfolio, return on assets, age, size, and product of microfinance are variables significantly affecting the social outreach of microfinance in Ethiopia. The study found that microfinance institutions are serving a fraction of the poor in Ethiopia. Microfinance institutions in Ethiopia need to maintain the momentum and trends of depth and breadth. MFIs need to accelerate their progress in order to reach more of the poor.

The study examined the impact of exchange rate and interest rate on stock prices in Nigeria using monthly data from January 1996 to December 2022. The key variables of interest were interest rate, exchange rate, and stock prices. The study also employed other variables like the oil price and inflation as control variables (given their important considerations to equity investors). The Autoregressive Distributed Lag (ARDL) estimation technique was adopted, and the result revealed that no long-run impact exists between the all-share index, exchange rate, and interest rate. However, in the short run, the oil price and exchange rate in the previous period and the all-share index in the previous period were significant in explaining the all-share index. In addition, the relationship between the exchange rate and the all-share index was negative, while the oil price has a positive relationship with the all-share index. Thus, it is important for the monetary authority to ensure the stability of the naira in order to encourage investors, thereby reducing the volatility of their investment and enabling investors to make informed investment decisions.