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This paper analyzes the effect of Bank of Japan’s implementation of negative interest rate policy on various macroeconomic indicators – the Nikkei Stock, unemployment rate, foreign exchange rate, gross domestic product (GDP), and inflation rate – in a pre-and-post analysis. The implementation of negative interest rates was in response to conventional monetary policy having little to no effect after the financial crisis of 2008. The Bank of Japan was not the first central bank to implement negative interest rates; however, it is only one of six central banks to do so. For this reason, literature in unconventional monetary policy, specifically negative interest rates, is limited. In this paper, we find evidence that movements in the Nikkei 225 Stock, the exchange rate, unemployment, and GDP coincide with movements expected under conventional monetary policy. We also find evidence of statistically significant impact on GDP and unemployment. However, we could not find evidence it had an effect on the inflation rate. Overall, this paper finds that the unconventional monetary policy of negative interest rates followed similar movements as that of conventional monetary policy.

More the capital more the industries can be lead to more employability. Hence, current paper aims to analyze the trend and pattern of FDI and its impact on the Indian economy using uses stepwise regression to select the appropriate variables with time series data over thirty years from 1992-2021 and found that there is a positive trend of FDI inflow into the country over the study period and the intersection between FDI and GDP is very high and the foreign exchange reserve is also very high, Moreover, foreign exchange reserves and interest rates have a significant relationship with FDI.

This paper aims to assess the impact of financial variables on output gap in a group of middle-income Asian countries such as India, Indonesia, Republic of Korea, Malaysia, and Thailand. In order to improve on the previous methodologies, this study followed a different approach by considering a binary nature of dependent variable. In order to explore role of credit guarantee, this paper considered credit guarantee to credit offtake ratio as an explanatory variable in defining output gap. Moreover, in order to get a clear picture on influence of monetary and fiscal policy, we have included revenue deficit and debt to GDP ratio along with real interest rate and inflation rate. Our Probit model ultimately proves that credit guarantee is an important factor for identifying output gap. Additionally, output gap is found to be neutral towards the movement of other financial variables.

This paper proposes to analyze the poverty rate in the eight development regions of Romania (NUTS 2), in the period 2010-2019. To provide the most complex analysis possible, I examined the determinants of the poverty rate, and I concluded that the gross domestic product per capita and the gross value added of the ICT sector reduce the poverty rate, while the unemployment rates lead to poverty increases. However, at regional level, in general, the poverty rate decreased in 2019 compared to the 2010 levels.

The role of saving in promoting economic growth has received considerable attention all over the world. Saving is considered as real driving force behind the growth of an economy. The aim of this paper is to examine the casual relationship between economic growth and savings in India. To analyze this relationship time series data from 1960 to 2019 was used. To check the stationarity of data ADF and PP test were used. The Johansen co-integration test was employed to check the relationship between the variables. Finally Granger causality test was applied to see the direction of causality. The results have shown that all the variables are non stationary. The Johnson method shows that both the variables share the relationship with one another. The econometric evidence supports that savings do cause economic growth and economic growth in turn to savings. The bi-directional casual relationship was observed, which suggests that in India higher economic growth leads to higher savings and higher savings to more economic growth.

In this paper, the author attempts to verify, on the basis of a selected set of data, if the influence of the causal variables (taxation indicators), namely Taxes on production and imports less subsidies and Taxes less subsidies on products on the Gross Domestic Product falls under the category of Granger causalities, and the research hypotheses are defined accordingly. Since the variables were supposed to be, and actually found to be non-stationary, the chosen research method is based on the Toda-Yamamoto approach, adapted to the structure of the data. The results allow the validation of the hypotheses in a limited number of cases, the analysis aimed to test the causalities between the nominal values and, on the other hand, their elasticities.

Unemployment is one of the most prominent issues being faced by developing countries especially India. Unemployment means productive resources not being utilized at all, which results low growth rate in real GDP. In macroeconomic terminology this relationship is called as Okun’s Law. The main aim of this paper is to examine whether there exists an Okun type relationship in Indian economy or not. Empirical result shows negative and significant effect of growth upon unemployment rate. Our model suggests that 1% increase in GDP will decrease unemployment rate by 0.4 percentage point.

This paper aims to analyze the influence of Unbalanced Economic Growth on Dynamic Trade Specialization. We analyze the effects of unbalanced economic growth to the dynamic trade specialization with the econometric model. The countries of Argentina, Brazil, Paraguay and Uruguay are the units of analysis in this research. The results obtained the country Argentina and Brazil possesses positive relations and significantly affect dynamic trade specialization, but not for the country Paraguay and Uruguay. In addition, the world unbalanced economic growth has a relationship that does not significantly affect the Dynamic trade specialization of all countries selected in this research.

The purpose of this paper is to analyze the impact of the accession of our country to the EU based on the economy. The economic indicators analyzed are gross domestic product, budget deficit, government debt, government spending, government revenue, export and import. The analysis involves creating a multifactorial regression model with a dependent variable (gross domestic product) and as independent variables all other sets of data. Also, Granger\’s causality will be used to study the relationship between variables. The model results indicate a direct relationship between gross domestic product and the share of government budget deficits, the import on the gross domestic product, and an inversely relationship between gross domestic product and the shares of government debt, Government revenues and exports in the gross domestic product.

This paper investigates the long run impact of GDP and tax revenue on public health care expenditure using panel FMOLS and DOLS models for sixteen major states of India over the period 1980-2013. This study is more relevant in order to measure the progress in universal health care financing across the states of India because states are heterogeneous in terms of health care spending, associated with low tax bases and low level of GDP growth. The empirical result shows that health expenditure, GDP and tax revenue are cointegrated in the long run. There is a positive and significant impact of income and revenue generation on growth of health care expenditure while the elasticity of health care expenditure is less than one. The result implies that there is state level heterogeneity in the share of medical and public health care expenditure to income in India. These research findings would serve as effective policy instruments to measure the progress towards universal health coverage among the states of India.

This paper basically highlights the determinants factors of FDI and how these factors are affecting FDI which is the most important factors of economic growth. It includes GDP as a dependent variable and FDI, Trade Openness and Exchange rate are the independent variables. This study has used time series data which are from various secondary data sources like IMF, RBI etc. and installed ADF test for checking the stationarity of the data. It has also used Johnson Co-integration test for find out the long run relationship between the dependent variable and independent variables. Signifying the fact that all the variables of the study move together in the long run. If variables are co integrated, the slope coefficients becomes super consistent. Among the long run coefficients, the influence of GDP to inward FDI is the highest which is 2.276. This indicates the role of market size in attracting foreign capital flow.