Commitment to capital raising for venture capital funds in India: An Application of ARDL Model

Venture capitalists (VCs) áourish on the ability to add funds to their kitty across nations. Consequently, VCsíability to convince Limited Partners (LP), who are their primary source of Önancing, plays a critical role in the venture capital investment growth in any economy. However, it is not easy to rake in capital from an investor. LPs assess the market conditions carefully before making their capital available to the VCs. This paper examines the macro-economic variables that ináuence the supply of money to venture capital funds in emerging economies such as India from an LPs perspective. The empirical analysis using Autoregressive-Distributed Lag (ARDL) approach reveals that supply of capital to the VC funds in India is ináuenced by macro variables as well as past investment behaviours. Macro-variables such as GDP growth, interest rate spread, global liquidity, and ináation rate signiÖcantly ináuence the supply of capital to the VC funds in India. However, stock market liquidity does not ináuence the supply side of the venture capital investment. Our analysis reveals that VCsífund raising in India is highly ináuenced by their past investment relation with the LPs.

A mixture autoregressive model based on Gaussian and Student’s t-distributions

We introduce a new mixture autoregressive model which combines Gaussian and Student’s t mixture components. The model has very attractive properties analogous to the Gaussian and Student’s t mixture autoregressive models, but it is more flexible as it enables to model series which consist of both conditionally homoscedastic Gaussian regimes and conditionally heteroscedastic Student’s t regimes. The usefulness of our model is demonstrated in an empirical application to the monthly U.S. interest rate spread between the 3-month Treasury bill rate and the effective federal funds rate.

Assessing effects of Interest Rates Spread on Non-Performing Loans: A Case of Commercial Banks in Trans-Nzoia County, Kenya

In the spike of increasing occurrences of non-performing loans among commercial banks in Trans-Nzoia County, Kenya, interest rate spread should be given serious consideration through more empirical research. This study therefore sought establish the relationship between the interest rate spread and occurrence of non-performing loans among commercial banks in Trans-Nzoia County. It specifically; looked into the credit risk management impacts non-performing loans, bank regulation impacts non-performing loans, and the capital sufficiency impacts non-performing loans. Adopting descriptive research design, the study used the 78 employees of commercial banks in Trans-Nzoia County as its targeted. The entire population participated in the study as respondents. Data, which was gathered using a questionnaire, was using quantitative approach to yield descriptive and inferential statistics. Multiple regression analysis was used to draw inferences from the findings. All factors were found to be statistically significant (p,0.05). Thus, credit risk management, bank regulation impacts, and the capital sufficiency have a positive significant effect on non-performing loans among commercial banks in Trans-Nzoia. The study recommended for; credit staff training programmes, applying strict interest rate rules and strict lending advances policies. In the spike of increasing occurrences of non-performing loans among commercial banks in Trans-Nzoia County, Kenya, interest rate spread should be given serious consideration through more empirical research. This study therefore sought establish the relationship between the interest rate spread and occurrence of non-performing loans among commercial banks in Trans-Nzoia County. It specifically; looked into the credit risk management impacts non-performing loans, bank regulation impacts non-performing loans, and the capital sufficiency impacts non-performing loans. Adopting descriptive research design, the study used the 78 employees of commercial banks in Trans-Nzoia County as its targeted. The entire population participated in the study as respondents. Data, which was gathered using a questionnaire, was using quantitative approach to yield descriptive and inferential statistics. Multiple regression analysis was used to draw inferences from the findings. All factors were found to be statistically significant (p,0.05). Thus, credit risk management, bank regulation impacts, and the capital sufficiency have a positive significant effect on non-performing loans among commercial banks in Trans-Nzoia. The study recommended for; credit staff training programmes, applying strict interest rate rules and strict lending advances policies.

The Impact of Financial Intermediation on the Economy of Ghana

This study investigated the impact of financial intermediation on economic performance using data from sixteen (16) universal banks in Ghana. This investigation is carried out using five popular indicators of financial sector intermediation, which are deposit mobilisation, customer credit, operating cost, reserve requirement and interest rate spread. Gross Domestic Product Per Capital (GDPPC) was used as a measure of economic sector growth or performance. The causal research design was used in this analysis. The unit root was estimated using the Augmented Dickey Fuller (ADF) test. The relationship between the dependent and independent variables was also determined using basic statistics tests and multiple regression analysis. The results reveal that bank deposits have an insignificant positive effect on the economy. Bank credit, however, has a negative significant effect on economic growth. The results also suggest that operating cost has a negative effect on the economic growth but the result is not significant. However, bank reserves have a positive significant effect. Finally, the results suggest that interest rate spread has a positive effect on the economy, but the relationship is not significant.

The Consequence of Credit Performance and Capital Adequacy: Evidence from Commercial Banks in Nepal

Following random effect GLS model, this study aims at examining the consequence of credit performance and capital adequacy of Nepalese commercial banks. For the analysis, the balanced panel data of 19 commercial banks have judgmentally been selected and used. The researcher took credit to deposit ratio (CDR), interest rate spread (IRS), non-performing loan ratio (NPLR) and capital adequacy ratio (CAR) as the predictors of profitability measured by return on assets (ROA) of the banks. The results indicate that the study predictors are significant in defining variation on ROA. The variables CDR and NPLR have significant negative impact on ROA. In contrast, the predictors IRS and CAR have positive consequence on ROA. However, the relationship between CAR and ROA is statistically insignificant. Results of the study can contribute as an important input to regulatory body in developing policy so as to make banking operation effective.

EFFECT ANALYSIS OF BANKING SECTOR REFORM AND GROSS MANUFACTURING OUTPUT IN NIGERIA: IMPLICATIONS FOR ACHIEVING SUSTAINABLE DEVELOPMENT GOAL 9

No doubt, structural transformation lies at the heart of economic progress of any nation. Most significantly, the industrial sector, especially manufacturing, is a key engine of growth and development. Unfortunately, manufacturing development in Nigeria, over the years have not improved despite the banking sector reforms. This paper empirically investigated the shock effects of the banking sector reform on gross manufacturing output in Nigeria between the period 1970-2018. The variables used in the paper include gross manufacturing output, bank credit to the manufacturing sector, interest rate spread, nominal exchange rate, market capitalization, manufacturing capacity utilization and a dummy variable. The data were sourced from the Central Bank of Nigeria Statistical Bulletin, International Monetary Fund Financial Reports and the World Bank Development Indicator (2019). The Vector Autoregressive Model (VAR) estimation techniques were employed to achieve the objective of the paper. The results showed that gross manufacturing output responded negatively to bank credit during all the reforms phases. It further revealed that it responded negatively to a unit shock in exchange rate during the pre-SAP and bank recapitalization periods, but positively during the deregulation, regulation and liberalization periods. It showed also that gross manufacturing output responded negatively to shock in interest rate spread during all reform phases in Nigeria. The policy implication of these findings attested to the fact that the linkage between the banking sector and real sector is weak in Nigeria. Hence for Sustainable Development Goal 9, in particular 9.2, to be achieved, the linkage between both critical sectors must be integrated and strengthened via improving on the banking sector fundamentals and introduction of shock measures from the reform.

The financing strategy of agricultural supply chain based on cost sharing and buyer guarantee is considered in smart agriculture

Supported by the agricultural technology, the intelligent agricultural development is flourishing. However, due to the high technology cost and investment risk, intelligent agriculture in China is still in the exploration stage. This article designs the appropriate cost sharing mechanism under the two-stage supply chain system, which composes of a farmer, a core enterprise and a commercial bank. With the comparison between commercial bank financing model and the buyer guarantees financing model, this paper researches the optimal decisions of supply chain members and the influence of the cost-sharing ratio, technical input gain effect and the buyer guarantees ratio. The results show that the profit will increase with the add of technical input gain effect. Besides, only under certain conditions, cost sharing is valuable to each member. Finally, numerical examples show existing an optimal interest rate spread area that all members would benefit from the buyer guarantee financing model.