This study analyses tax compliance among firms in Sub-Saharan Africa (SSA) within an extended Slippery Slope Framework (eSSF). It applies instrumental variables and generalized estimating equations models on a constructed World Bank’s Enterprise Survey longitudinal dataset. The results indicate that the perceived power of the tax authorities does not influence firms’ tax compliance, which could be linked to corruption in the form of informal payment. The results also show that corruption encourages the culture of tax non-compliance among firms in SSA because the defaulting firms bribe tax authorities in order to avoid paying taxes and being punished for that. In addition, the results demonstrate that the perceived trust of tax authorities (state representatives) is vitally important in encouraging tax compliance among firms in SSA. In terms of political decisions, it may be implied that gaining trust of taxpayers should be pursued.
This study investigates the asymmetric impacts of changes in inflation rates on the US bond rates. This investigation is constructed on the Fisher Equation. To this end, the nonlinear ARDL model is applied. Empirical findings indicate that only the decreases (π−t) in inflation rates affect bond rates. This asymmetric impact therefore shapes the FED’s monetary policy in terms of determining the bond rates at lower cost. When the inflation rate rises, the FED will know (in advance) that they do not need to increase the bond rates. This reminds us the FED’s former pre-emptive strike policy against inflation.
This study is a comparative analysis of the effects of money and capital markets on the Ghanaian economy covering the period from 1991 to 2017 using the dynamic Auto Regressive Distributed Lag (ARDL) framework. Empirical results confirmed the existence of a unique and stable long-run relationship between the money market, capital market and economic growth. In respect of money market indicators, findings confirmed that monetary policy and treasury bills rate have had negative but significant impact on growth in the short- and long-run respectively. More so, total liquidity negatively and significantly influenced the Ghana-ian economy both in the short- and in the long run. Both market capitalisation and total value of stock traded, as proxies of capital market, had positive and significant effects on short-run growth, while both indicators as well as stock market turnover negatively and insignificantly affected long-run growth. This means that capital market exerts a short-run impact on the country’s economy, while money market exerts both short- and long-run impacts. The lesson relearned is that the money market propels the Ghanaian economy better than the capital market.
This paper evaluates the accuracy of forecasts for Polish interest rates of various maturities. We apply the traditional autoregressive Diebold-Li framework as well as its extension, in which the dynamics of latent factors are explained with machine learning techniques. Our findings are fourfold. Firstly, they show that all methods have failed to predict the declining trend of interest rates. Secondly, they suggest that the dynamic affine models have not been able to systematically outperform standard univariate time series models. Thirdly, they indicate that the relative performance of the analyzed models has depended on yield maturity and forecast horizon. Finally, they demonstrate that, in comparison to the traditional time series models, machine learning techniques have not systematically improved the accuracy of forecasts.
This paper examines the causal relationship between nutrition intake, health status, education and economic growth within a six-variate VEC framework, forecast error variance decomposition and impulse response function techniques, covering the period from 1990 to 2013, using quarterly data in Nigeria. This paper includes control variables in order to eliminate variable omission bias, unlike most existing studies. The results suggest the presence of long-run, bicausal relationships between the candidate variables of the study. In addition, the short-run unidirectional causal relationships are found between main variables, including a causal relationship running from nutrition and fiscal policy to education, as well as a causal link running from education and economic growth to health status. These findings support the existing theories. The results based on the model and empirical data suggest that the government should allocate more resources to human development in order to enhance productivity and boost economic growth. Similarly, there is a need to design adequate mechanisms to ensure proper allocation of the limited resources and avoid their embezzlement by corrupt government officials.
In this study, we attempt to examine the factors that explain the spatial price differentials of selected perishable food crops across Nigerian markets. Based on monthly market prices of onions and tomatoes across different States, we examine the implications of climatic variations, cost of transportation and differences in economic sizes on the price spread of these items. The empirical findings from the dynamic heterogeneous panel regressions show that these factors have significant long-run impacts on the difference in food prices across markets. The results highlight climatic differences and transportation costs are important factors in regional price spreads for agricultural commodities and hence the need for specific policies to reduce the prices variability. Policies geared towards improving agriculture value-chain could o er pathways towards mitigating food loss and waste associated with changing climate and transfer costs, and thereby reduction in prices.
The multiple indicators multiple causes (MIMIC) framework is used to analyze dimensions related to causation and indicators of tax haven status. Robust results were obtained that identify a country’s tax burden and area as causes of a country adopting policies usually observed in tax havens. The level of social security contributions as a proportion of public revenues and the ratio of indirect to direct taxes were found to be statistically significant indicators of tax havens. Data from 68 countries for more than twenty years were analyzed, enabling the results to contribute to a deepening of the current debate about tax havens and their socio-economic profiles.