How Economic Growth Can Be Affected: Analysis for Romania - Research Proposal Example

How Economic Growth Can Be Affected? Statistical Analysis for Romania al affiliation For the research, quarterly data presented by the National Institute of Statistics and the National Bank of Romania for the years 2001-2009 was applied. As a research methodology, the backward mode of linear regression that consists of frequentative elimination of the explanatory variables that possess the most relevant impact on the dependent variable into the SPSS program The variables applied in the data set include: Economic growth rate: as per this study, the economic growth rate is taken as the quarterly growth rate of the GDP. It presented as the dependent variable of the data set. The total credit bil RON: total credit bil RON in the study presents the full amount of credit advanced by banks to debtors within the domestic economy in Romanian currency. The average exchange rate RON/EURO: as per the study, the exchange rate is the rate at which the Romanian currency exchanges against the Euro. The rate of inflation is the persistent increase in the cost of both consumer and producer goods and services. The resultant constant increase in prices arises from too much demand chasing few commodities in the market. The data set is important since it presents the journey taken by a transition nation as it experienced various stages of economic growth. From theory, it is normal for a country to go through periods of boom and depression, a pattern that is depicted by Romania between the years 1997-2009. During the boom sessions, the country saw an increase in credit and increased expenditures (López-Rodríguez, & Bolea-Gabriel, 2012, p. 111). However, during the periods of recession, the opposite occurred, and the country saw massive cases of unemployment and reduced aggregate demand. Report On the Data Set. As indicated in the Romanian statistical yearbook, following a decline period from 1997-2001, the country’s level of economic growth showed an increase starting 2002. Amongst the most significant factors that could create the growth, include increasing activity from service, construction, and industrialization (Danut, 2011, p. 112). Ultimately, the resultant increases in economic growth saw increase levels of final consumption. In addition, individual household consumption registered high increases characterised by the increasing volumes of goods sold. The goods were sold via retail trading activities and the populace service activity (Mutascu, & Danuletiu, 2011, p. 96). Additionally, the gross fixed capital formation particularly the extents of investment recorded remarkable improvement. The reported level of economic growth beyond 2001 grew from significant increments in the values of deficit current account. The rising deficits in the current account are partly attributable from the rising volumes of imports of goods and services relative to the exports of the same. The rate of growth for the Romanian economy after the year 2004 is the fastest for the country since 1989. It grew from active agricultural and construction industries that recorded growth rates of 22 and 9 percent respectively (Goschin, 2013, P. 656) The year marked a significant breakthrough in the Romanian economic cycle. Inflation rate began to descend rapidly which also created declines in the value of the RON/EURO exchange rate, on the grounds of rising external deficit (Enache, 2009, P. 504). The resultant economic growth rate was attained partly from the increased imports compared to the levels of exports. After the dwindling of the economy in 2007, the year 2009 reported even worse results. Combined with the substantial contraction of the economy and worrying levels of unemployment, the Romanian currency entered a phase of pressure (Enache, C. 2009, P. 509). Arguably, credit debts rose unexpectedly while the credit levels in the country sunk massively. Risk averseness of investors and curtailed financing from banks took the blame for the stagnated growth. Consequently, the continued the worrying performance of trade and capital growth saw the IMF in 2010 revising down the projections of Romanian’s economic growth from 0.8 percent to 0 percent. It is also this period that Barclays bank of the United Kingdom projected that Romania would undergo the worst recession ever. For 2010 financial period, economic and fiscal analysts estimated that the average growth of the county oscillated at 1 percent ((Mutascu, & Danuletiu, 2011, p. 96). As shown in figure 1, the period between 2001-2007 saw the Romanian economy registering a decelerating trend. Easing from 40.06 percent at the close of business in the first quarter of 2001 to 3.79 percent as business closed for the third quarter of 2007. The performance was then preceded by a slight increase to 4.99 percent by the third quarter of 2007, gaining several points to 8.56 percent at the close of business in 2008. The slight improvement was, however, short-lived and cut short by a decline to 45.6 percent at the conclusion of the last quartern of 2009. Among the factors attributed to the ease in the level of inflation during 2009 financial year are deficits in demand coupled with the fluctuations in the exchange rate. The attributes were to a great extent alluded to the unfavorable influence of demand. However, the effect of the rising demand for tobacco products being the most dominant factor (Robu, & Ciora, C. 2010, p. 310).The negative influences of the stagnated economic activities, galloping inflation coupled with the depreciation of the country’s official currency created by a diminution in the demand for credit. Also affected was the quality of debts portfolio owned by credit agencies to non-bank customers. With the beginning of the global financial crisis, Romania has continued to experience an increase in the levels of debt registered with credit agencies. The feature leads to firms reducing productivity as others wound down as the economy became unfavorable for business. Loan providers began to limit the amount of credit extended to clients. The limit introduction necessitated as the effects of the crisis continued to trickle. The strategy was a means of assuring that debtors could pay back the owed amounts (Bleotu, & Manoiu, 2013, p. 75) Figure 1. Economic growth rate in Romania from2001-2009 However, deep to the mid of the year 2009, the cost of created eased significantly due to the monetary policy interest of the NBR. The NBR introduced reductions in rates from the start of May 2009. However, experts argued that the policy lead to an increase in the security demands by financial providers (Bleotu, & Manoiu, 2013, p. 76). Applying SPSS software entails a statistical analysis of the correlation between the dependent variable and the independent variables. The aim is to obtain the coefficient to be used in the regression equation that shows the association amongst the variables of the research. The correlation analysis between the levels of economic growth rate as the dependent variable during the explanatory variables as earlier provided include data for the total credit value, the exchange rate and the rate of inflation. Discussions Possible Research Questions The data set analyzes the need to study some of the factors that could have led to the dismal performance of the Rwandan economy during the periods 2001-2009. In achieving this aim, the following research question could have probably been asked by the study. RQ: To what extent does the rate of inflation, the exchange rate and the total amount of credit affect the level of economic growth? From the given data set and the stated research question, the following research hypotheses are formulated. H1: economic growth is not affected by the prevailing rate of inflation H2: The average exchange rate does not determine the level of economic growth H3: The aggregate level of economic growth does not depend on the total volume of credit in the economy. Typically, the linear regression inclines to the calculation of the Pearson correlation constant for the variables provided in the data set. The linear regression is applied since it shows how the level of economic growth has been affected by the explanatory variables. As provided in the report section, data analysis applies the backward method in the linear regression. The method eliminates at every step the independent variables that demonstrate the weakest impact on the level of economic growth. Correlations Economic growth Average rate exchange RON/EURO Inflation rate Total credit value bil RON Pearson Economic growth 1.000 -.360 .130 -.535 Correlation Average rate exchange RON/EURO Inflation rate -.360 1.000 -.742 .507 .130 -.742 1.000 -.613 Total credit value bil RON -.535 .507 -.613 1.000 Sig. (1-tailed) Economic growth . .016 .226 .000 Average rate exchange RON/EURO .016 . .000 .001 Inflation rate .226 .000 . .000 Total credit value bil RON .000 .001 .000 . N Economic growth 36 36 36 36 Average rate exchange RON EURO 36 36 36 36 Inflation rate 36 36 36 36 Total credit value bil RON 36 36 36 36 In the SPSS Analysis, all the independent variables proved to a have a significant relationship with the level of economic growth, as such, none of them was eliminated. However, based on the theory, despite the existence of some form of association between the variables, the ensuing relationship is established to weak. The correlation coefficient is set at 0.681. The level of significance is established below 0.05 implying that minor errors determined by chance are evident in the estimation of the relationship. Of the independent variables, only the total credit influence on the economy is established to have a firm impact on the level of economic growth. Table 1 The correlation coefficients and the significance for the dependent and independent variable. From the table, at 5 percent significance level, the correlations are established as provided. As earlier provided, the level of economic growth was set as the dependent variable. The dependent variable is explained by the degree of inflation, the exchange rate and the total credit value in bil RON. A total of 36 indicators were entered in the SPSS data set. From the table, The relationship between economic growth and the level of inflation is established at .130 at a significance of 0.226. However, since the degree of significance is set at 0.05, it is, for this reason, to conclude that the relationship between the rate of inflation and the level of economic growth exists is not significant. As such at 5 percent level of significance, we accept the hypothesis that the level of economic growth is not dependent on the level of inflation. The results are consistent with the theory, which provides that inflation and economic growth are indicators that never meet (Ionescu, Nitu, & Croitoru, 2014, p. 193). They argue that in as much as inflation reduces the value of money making it hard for the poor to afford goods and services, the incompatibility between inflation and economic growth is because inflation affects all sectors of the economy. For instance, an increase in the CPI is an indication of inflation. The CPI is applied as an index for contracted prices and is carried out as an adjustment to the effects of inflation. The second relationship is between the level of economic growth and the average exchange rate. The Pearson correlation is established as -0.360. The results are an indication that that a negative relationship exists between the average exchange rate and the level of economic growth. Checking on the resultant level of significance of 0.016 against the set level of 0.05 show that a significant relationship exists between the average exchange rate and the level of economic growth. As such, the study rejects the not alternative hypothesis that no relationship exists between economic growth and average exchange rate. From theory, it is shown that the exchange rate has an influence on economic growth. A strong exchange rate is regarded as an indication of economic growth. For instance, a study sought to determine the relationship between the exchange rate and economic growth. The results showed that a 10 percent depreciation of the real exchange rate tends to create a 3.2 percent rise in the economy (Oncioiu, & Oncioiu, 2012, p. 182). However, in the short-run, a contractionary impact is observed such that the same magnitude of real depreciation would lead to a partially half- percent reduction in GDP. Nevertheless, in the long-run expansionary impact of real depreciation can appeal for considering the function of exchange rate policy a growth policy. For Romania, the need for the maintenance of external competitiveness coupled with the promotion of growth remains a fragile task for the country’s policymakers. It is so because it pertains the management of an exchange rate regime followed with other consistent macroeconomic policies. Finally, a relationship between the level of economic growth and the total credit value in bil RON was sought. The Pearson correlation is set at -0.535 implying an inverse relationship between the level of economic growth and the total credit value in bil RON. However, since the significance level is established at 0.00 against the set level of significance of 0.05, it implies that the results are insignificant. Model summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .682a .460 .414 3.554786 Predictor: (Constant), Total credit value bil RON, average rate exchange RON/EURO, Inflation rate Dependent Variable: Economic Growth In conducting the regression analysis, the correlation is established as .681 while the regression is found to be 46.4 percent. The regression value depicts that 41.4 percent of the dependent variable (economic growth) is explained by three independent variable. The results are an indication of a thin relationship between the economic growth and its indicators. The table below indicates the linear regression coefficients Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. (Constant) 29.850 7.649 3.903 .000 Average rate exchange RON EURO -4.925 1.881 -.508 -2.619 .013 Inflation rate -.322 .102 -.669 -3.160 .003 Total credit value bil RON -3.969E-5 .000 -.688 -4.177 .000 The linear regression coefficients Dependent Variable: Economic growth The histogram obtained is: Histogram. P-P standard residuals graph. In the provided figures that depict the histogram and the standard residuals graph, the residuals are presented and compared as per the normal law of distribution. Typically, a residual is an observable estimate of the unobservable error of statistics. According to convention, the residuals are expected to comply with the normal law of distribution. It is held so that the linear regression model can be applicable in the data analysis. For instance, the 0.6-0.9 interval, the residuals failed to comply with the typical distribution law, implying that the errors in this instance are higher. Conclusions From the analysis and the interpolations, the coefficients from the regression equation depict that given the data for the period 2001-2009, the following correlations are established Increasing the exchange rate by one unit leads a 4.9 percent drop in economic growth A unit increase in the rate of inflation leads to a 0.322 decline in the rate of economic growth. If the aggregate credit value were to rise by 12 million RON, economic growth rate is expected to ease by 3.96×10-5 percent. At this instant, the study can now answer the research question that challenged the pattern of the association between economic growth and the development of the credit market in Romania. It is apparent that the growth of private credit, the inflation rate, and the average exchange rate does not create a significance changes in the level of economic growth. The results concur with the findings of Burnete, (2006, p. 757). He sought to analyze the relation between credit market and the growth of the economy in 25 nations in transition of which Romania was among them. His study dismissed existing literature that previously held that a direct association exists between the developments in the credit markets and economic growth. As such, on the short run, the activity of credit, the rate of inflation and the evolution of the aggregate exchange rate in Romania have to be controlled. Controls are needed for there to be a positive influence on the level of economic growth in the country. Exploring the macroeconomic imbalances, the deficit in the consolidated market and the current account deficit of payment balance makes it hard to sustain the dynamic of the gross domestic product. The aspect typically holds at the global front that is characterized by uncertainties and degrees of prudence. Limitations of the Data Set As noted, the data set seeks to establish the relationship between the level of economic growth, the exchange rate, the rate of inflation and the level of credit. The study was conducted in Romania. It is seen from the study that most of the variables considered in the analysis are weak determinants of economic growth. The thin relationship between the dependent variable and the independent variables are attributable to various pointed out in the study. Firstly, as evident from the analysis, a weak relationship exists between the level of economic growth and the variables used in the study. Economists argue that string indicators include aspects such as the real gross domestic product, consumer price index, consumer confidence surveys, money supply and producer price index. The elements are vital because they tend to show actual trends in data relative to the ones applied in this study. The analysis, as a result, claims that the study could have used better indicators of economic growth rather than the ones applied in this survey. Secondly, the data set was made from National Institute of Statistics and the National Bank of Romania. Despite the fact that the two can be reputable sources of data, studies claim that such data sources tend to be subjective and biased. Such that, the data obtained in the analysis could be manipulated to fit the expectations of a given entity. In line with this limitation, it is vital to compare the data with other sources such as the World Bank and the IMF. Data is available from scholarly journals related to the attribute under study. Reference list Bleotu, V. & Manoiu, N. 2013, "Economic Growth and Cohesion in the Context of 2013 Romanias Territorial Regionalization", Knowledge Horizons.Economics, vol. 5, no. 4, pp. 74-77. Burnete, S. 2006, "Romanias economic policy: rulers wisdom will lead us", Journal of Organizational Change Management, vol. 19, no. 6, pp. 753-759. Danut, V.J. 2011, "Demographic transition and economic growth in Romania", Anuarul Institutului de Cercetari Economice "Gheorghe Zane" - Iasi, vol. 20, no. 2, pp. 103-112. Enache, C. 2009, "Fiscal Policy And Economic Growth In Romania", Annales Universitatis Apulensis : Series Oeconomica, vol. 11, no. 1, pp. 502-512. Goschin, Z. 2013, "The Remittances As A Potential Economic Growth Resource For Romania", Annales Universitatis Apulensis : Series Oeconomica, vol. 15, no. 2, pp. 655-661. Ionescu, A., Nitu, O. & Croitoru, G. 2014, "Signalling Economic Growth through Econometric Analysis: Romanias Case", Economics, Management and Financial Markets, vol. 9, no. 1, pp. 191-197. López-Rodríguez, J. & Bolea-Gabriel, C. 2012, "Geographical Economics and Per Capita GDP Growth in Romania*", European Research Studies, vol. 15, no. 3, pp. 109-133. Misztal, P. 2010, "Foreign Direct Investments, As A Factor For Economic Growth In Romania", Journal of Advanced Studies in Finance, vol. 1, no. 1, pp. 72-82. Mutascu, M.I. & Danuletiu, D.C. 2011, "Taxes and Economic Growth in Romania. A Var Approach", Annales Universitatis Apulensis : Series Oeconomica, vol. 13, no. 1, pp. 94-105. Oncioiu, I. & Oncioiu, F.R. 2012, "Impact Of Creativity And Innovation Of Smes On Economic Growth Development In The Knowledge Society In Romania", Institute for Business & Finance Research, Hilo, pp. 184. Robu, V. & Ciora, C. 2010, "The Impact of the Crisis Manifested In Financial Markets on Economic Growth. A Comparative Analysis of Romania and Bulgaria", Bulletin of the Transilvania University of Brasov.Economic Sciences.Series V, vol. 3, pp. 311-320. Read More