Error Correction Model Estimation Research Articles

Circular behavior of oil consumption and the impact of oil prices with the Fourier approach

In the changing world, oil continues to be important in energy production. Using monthly data from 1965 to 2022, the permanency of oil consumption fluctuations was investigated. Fourier-based Granger causality tests were used to examine cause-and-effect relationships between variables. Long-term relationships were estimated using Fourier-based Engle Granger cointegration tests. Unlike previous research, this study considers the long and short-term effects of countries that consume the most and least oil, as well as on a global scale, from different perspectives, examining oil price fluctuations together, and estimating these analyzes using the Fourier approach. Oil consumption fluctuations appear temporary in New Zealand and Luxembourg but permanent in all other countries. Oil consumption and prices share a causal relationship in the US, Japan, New Zealand, and Luxembourg, but no relationship elsewhere. A long-term relationship exists between oil consumption and prices in the US, India, Saudi Arabia, Russia, Japan, South Korea, Canada, Mexico, and Estonia. In other countries, no long-term relationship is found between these two variables. Error correction model estimation shows only the equation for Japan can be interpreted based on statistical significance. A one-unit deviation between oil consumption and prices can reach equilibrium in 20 months.

Effect of Remittance Inflow on Economic Growth of Nigeria

This study examined the effect of remittance inflow on economic growth of Nigeria. The study specifically analyzed the short run and long run of personal remittance inflow on annual growth rate of gross domestic product of Nigeria. The study focused on Nigeria over the period of 41 years spanning from 1981 to 2021.This study employed secondary time series data obtained from World development Index and Central Bank of Nigeria statistical bulletin. Data collated were analyzed by correlation analysis and unit root test, co-integration test, and Error correction model estimation. Result showed that on the short run remittance inflow exert insignificant negative effect on GDP growth of Nigeria (-0.337970, p > 0.05), while on the long remittance inflow exerts significant positive effect on GDP growth rate (1.973835, p < 0.05). This study established that inflow of personal remittance on the short run might be detrimental to the level of economic growth Nigeria if not channeled to productive engagement by recipients in the home country. Meanwhile on the long run, when the inflow rises consistently, the tendency to boost the level of economic growth is Nigeria is high and significant. Hence this study recommends the need for policies and programs as well as appropriate system reforms that encourage utilization of remittance for productive purposes. In addition there is need to put in place structure that will checkmate the rate of brain drain in the country, so as not to trade our quality human capital just for funds flow that might not necessarily be channeled equitably for productive activities in the short and intermediate term.

Tax Revenue and Economic Growth in Nigeria: A Bi-Directional Approach

The study examined the bi-directional effect of tax revenue and economic growth in Nigeria from 2011 to 2022 by employing total tax revenue and nominal Gross Domestic Product at current price. Data was extracted from 2011 to 2022 quarterly reports published on the website of the Central Bank of Nigeria, National Bureau of Statistics and Federal Inland Revenue Service. Unit Root test using Augmented Dickey-Fuller (ADF) test shows that at the first difference, the variables are stationary at 1%, 5%, and 10% level of significance while Engle and Granger co-integration test reveals significant evidence of a long-run relationship between the variables of the study’s models. Findings from Error Correction Model (ECM) estimation show that Total Tax Revenue has a positive and significant effect on Nominal Gross Domestic Product (t-stat 4.777; P-value 0.000) and Nominal Gross Domestic Product has a positive and significant effect on Total Tax Revenue (t-stat 5.552; P-value 0.000). The Granger Causality test revealed that there exists a positive and significant bi-directional effect between Total Tax Revenue and Nominal Gross Domestic Product in Nigeria. The study concludes that tax revenue has a positive and significant effect on economic growth and economic growth has a positive and significant effect on tax revenue. The study recommends that the government ensure continuous economic growth by providing human capital, security, employment, and foreign investment. This would increase the standard of living of citizens, increase tax payer’s income, and attract foreign investors who would pay tax on their income and properties.

Do expenditures on public health reduce preventable mortality in the long run? Evidence from the Canadian provinces

BackgroundInvestments in public health – prevention of illnesses, and promotion, surveillance, and protection of population health – may improve population health, however, effects may only be observed over a long period of time. ObjectiveTo investigate the potential long-run relationship between expenditures on public health and avoidable mortality from preventable causes. MethodsWe focused on the country spending the most on public health in the OECD, Canada. We constructed a longitudinal dataset on mortality, health care expenditures and socio-demographic information covering years 1979–2017 for the ten Canadian provinces. We estimated error correction models for panel data to disentangle short-from long-run relationships between expenditures on public health and avoidable mortality from preventable causes. We further explored some specific causes of mortality to understand potential drivers. For comparison, we also estimated the short-run relationship between curative expenditures and avoidable mortality from treatable causes. ResultsWe find evidence of a long-run relationship between expenditures on public health and preventable mortality, and no consistent short-run associations between these two variables. Findings suggest that a 1% increase in expenditures on public health could lead to 0.22% decrease in preventable mortality. Reductions in preventable mortality are greater for males (−0.29%) compared to females (−0.09%). These results are robust to different specifications. Reductions in some cancer and cardiovascular deaths are among the probable drivers of this overall decrease. By contrast, we do not find evidence of a consistent short-run relationship between curative expenditures and treatable mortality, except for males. ConclusionThis study supports the argument that expenditures on public health reap health benefits primarily in the long run, which, in this case, represents a reduction in avoidable mortality from preventable causes. Reducing public health expenditures on the premise that they have no immediate measurable benefits might thus harm population health outcomes in the long run.

The Impact of Government Expenditure on Industrial Sector Productivity in Tanzania

This study examines the impact of government expenditure on industrial sector productivity in Tanzania. The analysis was based on secondary annual time series data. Using data from 1980 to 2011, the study employs the Auto Regressive Distributed Lag (ARDL) bounds testing approach cointegration to examine the existence of long-run relationships and the error correction model (ECM) for the short-run relationships. All variables involved are integrated of order one while the error correction model estimates indicate the existence of a long-run relationship between government expenditure and the industrial sector productivity. Granger causality pair-wise test was conducted in determining the relationship among the variables. Analytical results show the existence of positive causality; therefore, government expenditure has significant impact on the industrial sector productivity. From a policy point of view, the focus should be on the government to adopt fiscal policy instruments with significant impact on industrial sector productivity.

How do energy consumption, globalization, and income inequality affect environmental quality across growth regimes?

This paper investigates the impacts of renewable and nonrenewable energy consumption, income inequality, and globalization on the ecological footprints of 49 countries for the period of 1995–2018. Panel cointegration test reveals a long-run relationship between the variables. Long-run parameter estimates derived from AMG and CCEMG, increasing income and nonrenewable energy consumption, have a significant positive impact on the ecological footprint, while countries that consume more renewable energy have seen an improvement in the quality of the environment. Conversely, neither income inequality nor globalization has a significant effect on national EFs. Evidence from the estimation of the panel threshold error correction model, where GDP growth is used as the transition variable, indicates a significant threshold effect, which supports a nonlinear relationship among the variables by identifying two distinct growth regimes: lower and upper. For the estimation sample, the positive and significant parameter estimates for economic growth in both growth regimes do not support the EKC hypothesis. The results indicate that renewable and nonrenewable energy consumption has a larger impact on the EF in the upper than lower growth regime. The threshold estimates are in line with the linear long-run estimates that do not indicate that income inequality has a significant impact on ecological footprint. However, globalization appears to negatively affect environmental quality in the lower growth regime.

The Relationship between Macroeconomic Variable in Indonesia: Study of Economic Growth, Export, Import, Labor and Inflation

The objective of this study is to assess the potential for mutual relationships and co-integration among variables such as economic growth, exports, imports, labor, and inflation in Indonesia, using secondary time series data covering the period from 1985 to 2022. The approach applied in this research involves the use of Vector Autoregression (VAR), encompassing Granger Causality and Johansen Co-Integration Test. Subsequently, Vector Error Correction Model (VECM) estimation and forecast analysis are conducted using Impulse Response Function, Variance Error Decomposition, and Forecasting. The results of the Granger Causality test indicate that there is only a unidirectional relationship between economic growth to imports, while there is no significant unidirectional relationship from other variables. The results of the Johansen Co-Integration test suggest that these variables have long-term relationships or are co-integrated. Based on the forecasting results, the research can be applied over the period from 1985 to 2037.

Long and Short-Run Effects of Climate Change on Boro Rice Productivity: An Empirical Evidence from Bangladesh

This study endeavors to examine the effect of climate change on Boro rice productivity in Bangladesh. Unit root, Co-integration and Vector Error Correction Model estimation technique are applied to measure the climate-crop yield interrelation on the basis of country level time series data for the period 1972-2019. Average maximum and minimum temperature, rainfall and humidity are used to attribute variables for climate change. The result of vector error correction model denotes that both in the long-run and short-run, average maximum temperature, average total rainfall and humidity negatively effect on Boro rice productivity in Bangladesh respectively. On the other hand, Average minimum temperature is positively effect on Boro rice productivity in the short-run. Fertilizer and irrigation have positive effect on Boro rice productivity in the short-run respectively. Conversely, labor has robust negative effect on Boro rice productivity in the short-run in Bangladesh agriculture. Policy maker should develop policies to mitigate temperature and introduce heat tolerant rice varieties and adaptation measure to sustain the Boro rice productivity in Bangladesh.

"Application of ARDL modelling in global structural shocks and their dynamic impact on FDI "

In general, sustainable economic growth is highly dependent on technological progress, managerial knowledge, and money supply in the economy. Globally, the COVID-19 pandemic has caused structural shocks to economic systems by increasing high economic uncertainty. For this reason, policymakers are exploring alternative measures to stimulate economic growth. And among these alternative measures we also find foreign direct investment, which represents an instrument widely used worldwide. There is a trend among foreign investors that they increasingly focus on the quality of institutions, especially on FDI policies in domestic countries. For this reason, governments of developing countries are increasingly adopting soft policies to attract FDI. Generally, the policies provide substantial taxation provisions. Thus, by stimulating foreign direct investment in global economic operations, short- and long-term growth is achieved. The beneficial effects of FDI are given by their unprecedented impact on achieving sustainability worldwide. The motivation of this study is to scale the effects of environmental quality and good governance on FDI inflows in European Union member countries for the period 2002-2021. We used the estimation of autoregressive distributed lag and error correction models to investigate the association and elasticity of explanatory variables on FDI inflows in EU member countries. Thus, as independent variables we use CO2 emissions from solid fuel consumption and the sum of exports and imports of goods and services. Environmental degradation comes from the depletion of resources by human activity, and ultimately this leads to increased costs and depletion of capital. As a result, environmental quality is crucial to the health of both people and businesses. In the recent economic booms, international trade needs serious attention to form new policies to invite more foreign investors. And as control variables we introduce Government effectiveness index and Gross capital formation. We introduce these variables because it is believed that weak institutional capacity can have a negative impact on economies. The study results suggest that government efficiency and a less regulated environmentally concerned economy drive capital transfer decisions.

Exploring the role of domestic and foreign factors in Indonesian Islamic mutual funds

Purpose — This study aims to test and analyze domestic and foreign factors' effects on Islamic mutual funds' long-term and short-term Net Asset Value in Indonesia.Method — The research is associative quantitative research. The data used is secondary data in the form of time series data for 2015-2022. Data sources were obtained from the Central Bank of Indonesia, the Financial Services Authority, and Yahoo Finance. Data analysis used time series econometrics with the Error Correction Model (ECM) approach.Result — The ECM estimation results show that in the long run, the money supply, the Jakarta Composite Index (JCI), positively affects the Net Asset Value (NAV) of Islamic mutual funds, and World oil prices hurt the NAV of Islamic mutual funds in Indonesia. In contrast, the World gold price does not affect the NAV of Islamic mutual funds. In the short term, JCI positively affects the NAV of Islamic mutual funds, and the World gold price hurts the NAV of Islamic mutual funds in Indonesia. Conversely, money supply and World oil prices do not affect the NAV of Islamic mutual funds in Indonesia.Contribution — This study makes a significant academic contribution by expanding the understanding of factors influencing the Net Asset Value (NAV) of Islamic mutual funds in Indonesia, addressing the research gap regarding the limited inclusion of variables, and suggesting the need for further exploration and comparative studies in different countries or regions.

Effect of bank credit on agricultural gross domestic product

Purpose. This study aimed to provide the central bank of Bangladesh with some empirical data on the impact of bank agricultural credit on agricultural output as a priority sector lending. 
 Methodology / approach. Econometric analysis is applied to discover the nature of the relationship between banks’ agricultural credit and agricultural gross domestic product (GDP) and to find the impact of bank agricultural credit on agricultural output in Bangladesh. Data are extracted from secondary sources, i.e., Bangladesh Bank, Bangladesh Bureau of Statistics, World Bank, and Ministry of Finance for 1991 to 2018. Time-series data are analyzed using the Augmented Dickey–Fuller (ADF) unit root test and the Johansen cointegration test and later examined with Vector Error Correction Model (VECM).
 Results. The Augmented Dickey–Fuller unit root test confirmed that the variables were non-stationary at their level data and became stationary after taking their first difference value. Since the variables are integrated at I(1), we performed the Johansen Co-integration test. Subsequently, one co-integration equation was found, and Vector Error Correction Model estimation was done afterwards. According to the results of VECM estimation, bank agricultural credit, pesticide consumption, and use of cropped areas have long-run relation with agricultural output. 
 Originality / scientific novelty. This study reveals the nature of relationship and assessment of the impact of bank credit on agricultural GDP with empirically valid techniques and tools. In this context, the data from Bangladesh remains very rare. Moreover, for those works which have been done in the context of Bangladesh, appropriate methods and techniques are not always inherent. Hence, this significant research gap is addressed in our present study. Thus, we expect that the findings of this study from Bangladesh based on empirically valid standard techniques can incrementally contribute to the existing literature.
 Practical value / implications. Findings of this research, can be used as an information basis by the central bank of Bangladesh. Based on the findings of this research, Bangladesh Bank should initiate new policies and programs regarding agricultural credit for the projected increase in agricultural GDP in Bangladesh.

Human capital and its impact on Ethiopian economic growth: ARDL approach to co-integration

Maintaining human capital at an optimal level is among the important mechanisms for ensuring steady economic growth. This study aims to examine the impact of human capital on Ethiopia’s economic growth. The study used the ARDL model applying annual data for the period 1980 to 2020. The ARDL-bound test was used to evaluate the presence of con-integration between human capital and independent variables. The study also applied the augmented Dickey-Fuller and Phillips-Perron unit root tests to check the stationarity of the variables. The test result presented that almost all variables become stationary after the first difference. Accordingly, the result from the bound test indicated the existence of a long-run relationship between the dependent variable and independent variables entered into the model. The estimated error correction model with a − 0.9528 coefficient also confirmed the existence of co-integration with a high speed of adjustment towards the long-run equilibrium. In the long-run real GDP, education expenditure, health expenditure, labor force, gross capital formation, total government expenditure, official development assistance, secondary school enrolment, consumer price index, drought, and policy change have astable long-run connection. The finding indicates an increasing ratio of health expenditure and secondary school enrollment should be designed, among others, to contain improved human capital in Ethiopia.

Effects of developmental and non-developmental expenditure on economics growth of India: An error correction model approach

In this article attempt is made to establish the relationship between the developmental and non-developmental expenditure in India and its influence over the economic growth. For this, secondary data are used for the period of 1991-2021 and sourced from various state finance reports, Ministry of Statistics and Programme Implementation, and World Bank, Indian Public Finance Statistics, and annual budget allocation. To check the long-run and short-run relationship among the variables Autoregressive Distributed Lag (ARDL) model, Bound Test and Error Correction Model techniques have been used. The ARDL estimates indicate that in the long-run development expenditure having positive impact over the economic growth, however, it is statistically insignificant. While population growth rate having negative impact over the economic growth. Further, Error Correction Model (ECM) estimates revealed that there is an existence of short-run relationship among the variables too and it is very sensitive, its adjustment rate is about 80 percent and statistically significant at 5 percent level. Therefore, it is suggested to the government to focus more on the short-run goals rather long-run issues because if the problems are address immediately at the time when it arises then it would also assist to achieve the long-run sustainable economic growth.

Projecting wheat demand in China and India for 2030 and 2050: Implications for food security.

The combined populations of China and India were 2.78 billion in 2020, representing 36% of the world population (7.75 billion). Wheat is the second most important staple grain in both China and India. In 2019, the aggregate wheat consumption in China was 96.4 million ton and in India it was 82.5 million ton, together it was more than 35% of the world's wheat that year. In China, in 2050, the projected population will be 1294-1515 million, and in India, it is projected to be 14.89-1793 million, under the low and high-fertility rate assumptions. A question arises as to, what will be aggregate demand for wheat in China and India in 2030 and 2050? Applying the Vector Error Correction model estimation process in the time series econometric estimation setting, this study projected the per capita and annual aggregate wheat consumptions of China and India during 2019-2050. In the process, this study relies on agricultural data sourced from the Food and Agriculture Organization of the United States (FAO) database (FAOSTAT), as well as the World Bank's World Development Indicators (WDI) data catalog. The presence of unit root in the data series are tested by applying the augmented Dickey-Fuller test; Philips-Perron unit root test; Kwiatkowski-Phillips-Schmidt-Shin test, and Zivot-Andrews Unit Root test allowing for a single break in intercept and/or trend. The test statistics suggest that a natural log transformation and with the first difference of the variables provides stationarity of the data series for both China and India. The Zivot-Andrews Unit Root test, however, suggested that there is a structural break in urban population share and GDP per capita. To tackle the issue, we have included a year dummy and two multiplicative dummies in our model. Furthermore, the Johansen cointegration test suggests that at least one variable in both data series were cointegrated. These tests enable us to apply Vector Error Correction (VEC) model estimation procedure. In estimation the model, the appropriate number of lags of the variables is confirmed by applying the "varsoc" command in Stata 17 software interface. The estimated yearly per capita wheat consumption in 2030 and 2050 from the VEC model, are multiplied by the projected population in 2030 and 2050 to calculate the projected aggregate wheat demand in China and India in 2030 and 2050. After projecting the yearly per capita wheat consumption (KG), we multiply with the projected population to get the expected consumption demand. This study found that the yearly per capita wheat consumption of China will increase from 65.8 kg in 2019 to 76 kg in 2030, and 95 kg in 2050. In India, the yearly per capita wheat consumption will increase to 74 kg in 2030 and 94 kg in 2050 from 60.4 kg in 2019. Considering the projected population growth rates under low-fertility assumptions, aggregate wheat consumption of China will increase by more than 13% in 2030 and by 28% in 2050. Under the high-fertility rate assumption, however the aggregate wheat consumption of China will increase by 18% in 2030 and nearly 50% in 2050. In the case of India, under both low and high-fertility rate assumptions, aggregate wheat demand in India will increase by 32-38% in 2030 and by 70-104% in 2050 compared to 2019 level of consumption. Our results underline the importance of wheat in both countries, which are the world's top wheat producers and consumers, and suggest the importance of research and development investments to maintain sufficient national wheat grain production levels to meet China and India's domestic demand. This is critical both to ensure the food security of this large segment of the world populace, which also includes 23% of the total population of the world who live on less than US $1.90/day, as well as to avoid potential grain market destabilization and price hikes that arise in the event of large import demands.

Oil Price Changes and Stock Market Performance in UAE: Evidence of Cointegration Persists in Economic Diversification era

The aim of this paper is to examine the linkages between stock market index, Dubai Fateh oil spot price, interest rate and FDI using monthly data on Abu Dhabi stock index for the period 2006- 2019. Vector Autoregressive Model have been employed to analyse the relationship between the variables. Using monthly data from 2006 to 2019, the results of Vector Error Correction Model (VECM) estimates suggest that there is long-run integration between oil price and monthly stock index series in which monthly oil prices have a positive impact on stock index. The Granger Causality indicates significant bidirectional causality running from ADX index, oil price and EIBOR. Meanwhile there is unidirectional causality from stock market index to FDI. Furthermore, Impulse Response Function was employed to examine market response to oil price shocks and our study reveals that UAE stock market is efficient as it responds immediately to the oil shock. These findings are relevant for investors for portfolio management and for the policymakers such that more aggressive economic diversification policies are initiated to wane the significant persistent oil-stock integration.

Correlation between tax revenues and gross domestic product: Evidence from the developing economy

This paper examines the relationship between tax revenues and the economic growth of Kosovo as a developing country. The paper uses quarterly time series data for 2010:Q1–2021:Q4 collected by the Kosovo Statistical Agency and the Ministry of Finance of Kosovo. The data were analyzed using EViews v10. Augmented Dickey-Fuller (ADF), Johansen cointegration test, vector autoregressive (VAR) model, vector error correction model (VECM) estimation, and Granger causality test was used to analyze the model. The VECM results showed that fluctuations in tax revenues have a negative effect on the gross domestic product (GDP) in the long run. Using data from nine countries, Nguyen and Darsono (2022) demonstrated that tax revenues have an adverse effect on economic growth. Using Granger causality, the results showed that tax revenue growth could cause GDP growth, and GDP growth can cause tax revenue. Okonkwo (2018) recommends that the government tighten tax collection methods and regularly evaluate tax policies to maintain the country’s tax revenue. Since taxes boost economic growth and boost taxes in emerging economies, the government should implement effective tax collection measures. The importance of the paper lies in the fact that fluctuations in tax revenues are an important cause of negative changes in GDP in the long run.

The Nexus Between Health and Economic Growth: Empirical Evidence from Indonesia

The controversial debate about the relationship between health and economic growth nexus has become one of the most contentious issues in the last two decades of scientific development. The inconsistency of research results that occur makes this hypothesis very interesting to study, especially in developing countries such as Indonesia. This study aims to determine the relationship between health variables such as healthcare expenditure, human development index, life expectancy, and mortality on economic growth with the Indonesian case study as the object of analysis. This study uses secondary data from Indonesia in the period 1985-2021 using the Engle-Granger Error Correction Model and Granger Causality. Based on the estimation of the Engle-Granger Error Correction Model, both in the long term and in the short term, all health variables have a significant influence on economic growth. To prove the causal relationship between health variables and economic growth, a causality granger analysis was used, it was found that healthcare expenditure had a causal (bidirectional) relationship with economic growth. Another causal relationship is also found in the human development index, the rest there is a unidirectional relationship between mortality and economic growth. This finding proved that health plays a crucial role on economic growth. Therefore, the government must be able to take several policies to improve the quality of public health including: prioritize development budget allocations for health infrastructure, implementing cash-transfer and health subsidies program to reduce cost-barriers that limiting healthcare access of poor people.

GOLD MINERAL EXPORTS AND ECONOMIC GROWTH NEXUS IN TANZANIA

Mineral exports have varied impact on economic growth among different mineral-rich countries. Some countries with abundant mineral resources have more sluggish economy than that without such resources. This study examined gold mineral exports and economic growth nexus by using time series data extracted from World Bank and Bank of Tanzania for the duration of 22 years from 1999 to 2020. The preliminary checks for unit root test show that economic growth and foreign direct investment are stationary at first difference while gold mineral export is stationary at level and first difference. Using autoregressive distributed lag (ARDL) and error correction model (ECM) estimation technique, the results show that in short run, gold mineral exports have negative insignificant impact on economic growth while economic growth has negative significant effect on gold mineral exports. The results imply that as economic growth improves, the need for domestic uses of gold in jewelry and financial investment increases, hence decreasing gold export magnitude. However, it should be investigated whether such inverse relationship between economic growth and gold exports is caused by an increasing gold smuggling or not.

Industrialization and Land Conversion in Indonesia

Along with increasing development activities and population growth, the need for land is increasing, such as for settlements, industry and facilities and infrastructure. On the other hand, the availability of land is relatively constant, causing land scarcity or excess demand. The existence of excess demand for land availability causes land use competition, which will lead to land conversion. The study aims to empirically examine the antecedents of land use change that occurred in Indonesia in the 1981-2018 period. This study aims to determine whether industry and population growth influence land conversion that occurred in Indonesia in 1981-2018. This study uses secondary data published by World Bank for the 1981-2018 period. This study analyzes the effect of population and industrial growth with medium to high technology on land conversion in Indonesia. In this study, the ECM method used was the Engle and Granger two-stage procedure method, namely by running The Engle-Granger two-stage procedure. This study applies the Error Correction Model (ECM) dynamic model. The use of dynamic models is important in economic analysis because dynamic specifications are concerned with the formation of models of an economic system related to changes in time. In ECM estimation, all variables in the study must be stationary. These conditions must be met so that the estimation results are not biased or do not show spurious regression results. The results empirically prove that the variable of industry has a significant effect in the short term on land conversion in Indonesia. Growth with medium-high technology including construction that occurred in Indonesia (INDUSTRY) was 1.64E-05 which means that an increase in industry of 1 percent will increase land conversion by 1.64E-05 percent in the short term. The novelty in this study is to use a variable ratio of agricultural land area, which is reversed mathematically to measure land conversion variables in Indonesia.

Effect of Selected Macroeconomic Variables on Budget Deficit in Kenya

Macroeconomic stability has been a concern to many economies as it shows the economic health of a nation. Kenya has had unsustainable and persistent fiscal deficit which has been phenomenal in the recent past despite several economic reforms being established in an attempt to stabilizing the economy. The study was informed by the persistent increase in the budget deficit in Kenya amidst economic stagnation and macroeconomic instability. This therefore led to an attempt to establish the effect of selected macroeconomic variables on the budget deficit in Kenya. The specific objectives were to determine the effect of interest rates; exchange rate; inflation and money supply on budget deficit in Kenya. The study sought to evaluate the significant effect of the selected macroeconomic variables on budget deficit in order to formulate the policy consideration to the economic problem. The study was guided by the Keynesian which was the main theory of the study. The Mundell-Fleming and Ricardian Equivalence theories were also employed as addition theories to back up the study. The study methodology was based on an explanatory design for time series data covering 30 years from 1991 to 2020. Autoregressive distributed lag error correction model (ARDL) estimation was adopted to analyze and infer results of the study. The CUSUM model stability test indicated that the model was stable and the model coefficient was reliable. Diagnostic test results showed there was no autocorrelation (p=0.1510>2.062), no heteroscedasticity (p=0.0903>21.47), and there was no multicollinearity (vif=1.34). Shapiro wilk normality test indicated that the variables of the study were normally distributed. The ADF unit root test indicated that there was unit root and co-integration test confirmed that the variables had a long run relationship. The findings of the study were: interest rate had a positive significant effect on budget deficit in the long run ( β_1=0.0404, <0.05); exchange rate had a positive significant effect on budget deficit ( β_2=0.4189, <0.05); inflation had a negative insignificant effect on budget deficit ( β_3=-0.001, >0.05). Money supply had a positive insignificant effect on Budget deficit ( β_4=0.00004, >0.05). The ARDL long-run results showed that the explanatory variables had Adjusted R2=0.4666 impact on the budget deficit and an F-statistics of 135.5802. The study therefore concluded that interest rate had a positive effect on the budget deficit in the long run. Increasing interest rates in the economy ends up driving budget deficit upwards in the long run. The same was true when the variable of concern is exchange rate. The study findings recommend that there is need for the government to ensure there is stability in macroeconomic variables. This is because there was a significant link between the budget deficit and the selected macroeconomic variables. A strive by the government to reduce budget deficit would mean an adjustment in macroeconomic variables to suit the purpose. These adjustments may include reducing the interest rate in the economy. A reduction in the interest rates in the economy would end up reducing the budget deficit.