Top PDF GOVERNMENT SIZE VERSUS GOVERNMENT EFFICIENCY IN A MODEL OF ECONOMIC GROWTH

There are at least three good reasons to conduct such an exercise. First, the decision on the size and the efficiency of government spending, though complex and of a dynamic nature, is certainly a joint decision. Analyzing one without the other is likely to be greatly misleading. 5 While there is a substantial body of theoretical and empirical work on the relationship between government spending and economic growth 6 , there is little on the role of government efficiency, a harder concept to grasp, and practically nothing on the joint choice of size and efficiency of government spending. 7 In Ghosh and Gregoruos (2008), and Devarajan et al. (1996), the authors go in this direction but focus on the existence of two public goods with different productivities. Both public goods are equal in nature. We consider a prior distinction between the two types of public spending. One demands an accumulation effort and the other doesn’t. We introduce two types of capital (public and private) and focus part of our analysis on the relation between the two. Moreover we analyze different attitudes from the government considering the possibility of a self-driven government. We support our analysis on the empirical evidence that we have very different governmental behaviors. Second, the burgeoning literature on corruption -or, more generally, “bureaucracy” -its determinants and consequences, has put forward interesting models and results but is still poorly connected to a general framework to analyze the larger issue of government efficiency as it relates to the size of government, growth and economic development. 8 Third, whereas the micro determinants of the efficiency of government programs have been widely examined, many conclusions are not generalizable and much more needs to be understood at the aggregate, macroeconomic level. After a review of the literature one is left with important questions unanswered, among them: why are some countries stuck in a “bad” equilibrium with low income levels, inefficient and large governments, while others display large but efficient governments that are associated to high personal income

A country´s performance is, in part, dictated by the size of its public sector and the efficiency level with which it uses its (typically scarce) resources. 1 It is, therefore, important from both an economic and policy points of view to evaluate the performance of the public sector and understand the determinants of public sector efficiency so as to maximize welfare but also to optimize investment projects and, in that way, propel growth forward. There has been an ongoing debate in the literature over the role and size of the government (Afonso and Schuknecht, 2019), mostly motivated by the substantial heterogeneity across countries in terms of the government spending. 2 This issue is even more relevant when governments face strict government budget constraints and most western economies are living in the secular stagnation phase for several years now, notably in the context of economic downturns and of scarce public resources.

Babatunde   and   Adefabi   (2005)   empirically   assesses   the   direct   effect   of   education   on   economic   growth   in   Nigeria   during   the   period   of   1970-­‐2003.   The   general   objective   of   the   study  was  to  investigate  the  long  run  relationship  between  education  and  economic  growth   in   Nigeria   between   1970-­‐2003.   The   methodology   used   in   the   study   was   Johansen   Cointegration   technique   and   Vector   Error   Correction   Methodology   followed   by   Leoning   (2002).   Babatunde   and   Adefabi   (2005)   consider   two   different   situations   in   their   model:   firstly,  they  considered  human  capital  as  an  independent  factor  of  production.  And  secondly   they   assumed   that   the   level   of   human   capital   instead   of   growth.   They   state   that   the   economic  growth  rates  perform  a  basic  role  in  the  determination  of  the  growth  of  output   per   worker   whereby   human   capital   affects   the   productivity   parameter.The   Johansen   Co-­‐ integration   result   establishes   a   long   run   relationship   between   education   and   economic   growth.  They  have  stated  that  awell-­‐educatedlabour  force  appears  to  significantly  influence   economic   growth   both   as   a   factor   in   the   production   function   and   through   total   factor   productivity.  

4 to deliver services to citizens and businesses, however the implementation of e-government systems goes further to the fundamental transformation of production processes in public sector. The World Bank (2015) has published one of the most widespread definition of e-government that states “e-Government refers to the use by government agencies of information technologies (such as Wide Area Networks, the Internet, and mobile computing) that have the ability to transform relations with citizens, businesses, and other arms of government. These technologies can serve a variety of different ends: better delivery of government services to citizens, improved interactions with business and industry, citizen empowerment through access to information, or more efficient government management”. Similarly, Riley, defining e- government as “a central theme in information society at all levels such as local, national, regional and global as well”, assumes that “e-government has, or can transform public sector internal and external relationships through the use of information and communications technology to promote greater accountability of the government, increase efficiency and cost effectiveness, and create greater constituency participation” (Riley, 2007: 1). As it can be seen from the definitions above, main target groups of e-government initiatives are governments and their constituents, citizens, businesses and employees. By parity of reasoning, e-government delivery models include four blocks as it shown on the Figure 1.

There is quite a lot of literature of economic theory about the importance of public debt on economic growth. Diamond (1965) describes a model that examines the long-run competitive equilibrium in a growth model and then explores the effects of government debt on that same equilibrium. The author concludes that taxes have the same impact on individuals living during a long-run equilibrium, whether they are used to finance internal or external debt. According to Feldstein (1985), in theoretical terms, if the stock of capital is initially at an optimal level, it is better to finance a temporary increase in spending through debt, because the excess burden of taxation depends on the square of the tax rate. When capital is below the optimal level, it is preferable to finance the amount of spending with taxation. These conclusions are taken from the relationship between capital intensity and the golden rule level: when capital intensity is less than the golden rule level, it implies that the government spending-labour force ratio is smaller than taxation per capita and therefore the increase of debt must be financed by taxation.

A related work by Wang and Abrams (2007a) explored the dynamic effects of government outlays on economic growth and the unemployment rate in the context of a VAR framework by utilizing data from 20 OECD countries for three recent decades. Relating to the government size-unemployment linkage, they concluded: i) positive shocks to government outlays raise the unemployment rate; ii) the effects of government outlays on unemployment vary with the types of outlays, e.g., transfers and subsidies generate a larger effect than government purchases; iii) there exists a unidirectional causality between two variables, running from government outlays to the unemployment rate; iv) how government finance its outlays does not influence findings. In their working paper series (Abrams and Wang, 2006; Wang and Abrams, 2007b; Wang and Abrams, 2011) employing different econometric techniques and data samples, they provided further evidence. They reached almost similar results confirming that government size moves positively with unemployment. Based on their findings, Wang and Abrams (2007b; 2011) hypothesized that the steady-state unemployment rate −that refers to the natural rate for the economy, so-called the NAIRU, in which the expected inflation equals to the actual inflation− is determined by government size along with various institutional factors unlike the short-run fluctuations in the unemployment rate that is influenced by business cycles and inflation shocks.

Table 3 shows an estimation of the base model and variations using fixed effects. The dependent variable used is a simple annual growth rate for the first two mod- els, a cumulative 5 year ”rolling window” overlapping growth rate for the middle two, and a cumulative 5 year non-overlapping growth rate for the final two. The explanatory variables are lagged one period for the annual growth rate and the 5 year non-overlapping models, while five periods of lag were used for the 5 year overlapping models, in order to account for autocorrelation. When compared to Checherita-Westphal & Rother (2012), the coefficients regressed mostly maintain their signal, size, and statistical significance. The changes are chiefly the loss of statistical significance for the openness and gross fixed capital formation vari- ables, and the rise in significance of the long term real interest rate and the savings variables. In these estimates, no control variable remains statistically significant across all models.

On the other hand, another strand of literature suggests that government spending could have a positive effect on economic growth if it involves public investment in infrastructure, but could have a negative effect if it involves only government consumption. Yet, previous studies have not reached a consensus on the relationship between government spending and economic growth, owing to their differences in the specification of econometric models, the measurement of government expenditures, and the selection of samples (e.g., (Agell, Lindh, & Ohlsson, 1997). As argued by (Abu-Bader & Abu-Qarn, 2003), typical regressions for explaining government spending or economic growth generally focus on the relationship between government spending and economic growth, rather than providing insight into the direction of causality. One popular approach to investigating the causal relationships between the two variables has been using the tests (Granger, 1969). Over the past decades many studies have applied the Granger causality tests to test the causal relationship between government spending and economic growth. ( Halicioĝluз 2003) applies the Granger causality tests to the Turkish data over 1960 –2000 and finds neither co- integrated nor causal relationships between per capita GDP and government spending shares. In contrast, several studies find evidence on the Granger causality running from national income to government expenditureз and thus provide support for Wagner’s law eйgйз(Abu-Bader & Abu-Qarn, 2003). In particular, (Dritsakis, 2004) provides evidence on such a causal relationship for Greece and Turkey. By applying the unit-root, co-integration, and the Granger causality tests to panel data, (Narayan et al., 2008) find that Wagner’s law is supported by the panel of sub-national data on юhina’s central and western provincesз but is rejected by the full panel consisting of all Chinese provinces. Using the U.S. data since 1792, (Guerrero & Parker, 2007) find evidence supporting Wagner’s law but not supporting the hypothesis that the size of the public sector Granger causes economic growth.

Devarajan et al. (1996) are of the opinion that the influence of public spending depends not only on their nature - spending productive, unproductive - but also the size of the percentage of GDP. The authors concluded that the present growth of public current expenditure has a significant and positive influence on economic growth. Capital expenditures have a negative impact on GDP per capita, and therefore these expenses, even if they are productive, used in excess, can become unproductive for the economy. Their empirical results showed that developing countries wrongly allocated public investments relying more on capital expenditure to the detriment of current expenditure.

Its Portuguese version did not exclude an active role of the government in fostering economic growth by means of building public works that corresponded to what [r]

ABSTRACT: This study aimed to investigate factors influencing the adoption of improved cultivars (ICs) in peach production in Khyber Pakhtunkhwa province of Pakistan. A total of 270 respondents were randomly selected from the three different cultivated areas of Khyber Pakhtunkhwa, namely, Peshawar, Nowshera and Swat. Binary choice model was used in this study to categorise the ICs of peach farmers into adoption and non-adoption. The study identifies that socio-economic, institutional farm resources, and climatic factors are influencing the adoption of ICs of peach production. Results of the estimated model reveal that farmer’s age, education, household size, membership, cell phone, farm size, extension services and the role of the non-government organization have a positive effect on adoption of ICs. In addition, farmer’s experience, off-farm income, livestock and machinery ownership, credit access and inputs prices have a positive and significant impact on ICs adoption. Moreover, results of the logit model demonstrate that climatic related factors have a highly significant and positive impact on the adoption of ICs. These results suggested that institutional services should be strengthened to provide managerial and technical skills on ICs technology adoption and on time provision of financial services to enhance the productivity of peach farmers.

The economic perspective brings forward the idea that the economic factors are the ones which mostly influence entrepreneurial activity (Wennekers et al., 2005). The relationship between variables of the macroeconomic environment and the rate of entrepreneurial activity has been extensively explored in literature. The burden of regulations such as, high costs of entry, and bureaucracy costs were proven to be obstacles to entrepreneurial activity (Klapper et al., 2004). Institutional features such as, the tax environment, government size, the level of trust, corruption, the level of financial development (Giannetti, 2003), market conditions such as size and growth (Davidsson et al., 1994) also impact upon the level of entrepreneurship development. The relationship between unemployment and entrepreneurship is an ambiguous one: some researchers argue that unemployment has a positive effect on entrepreneurship (Martinez-Granado, 2002) while others demonstrate that higher unemployment levels are associated with low entrepreneurial activity (Storey and Johnson, 1987).

Our paper includes several novel contributions: i) we construct a growth model allowing for an explicit government role, we characterize the conditions underlying the optimal path of the economy and determine the steady-state solutions for the main aggregates; ii) we analyse a wide set of 108 countries composed of both developed and emerging and developing countries, using a long time span running from 1970-2008, and employing different proxies for government size and institutional quality to increase robustness; iii) we build new measures of extreme-type political regimes which are then interacted with appropriate government size proxies in non-linear econometric specifications; iv) we make use of recent panel data techniques that allow for the possibility of heterogeneous dynamic adjustment around the long-run equilibrium relationship as well as heterogeneous unobserved parameters and cross-sectional dependence (e.g. Pooled Mean Group, Mean Group, Common Correlated Pooled estimators, inter alia); vi) we also deal with potentially relevant endogeneity issues; and vii) for an EU sub-sample we assess the relevance of numerical fiscal rules in explaining differentiated GDP and growth patterns.

By applying a threshold regression model to the King and Levine (1993a) data set Deidda and Fattouh (2002) find that in low income countries there is no significant rela- tionship between financial development and growth whereas in high income countries they find that this relationship is positive and strongly significant. In other words, financial de- velopment is not associated with higher growth rates at all levels of economic develop- ment. Results obtained by Rioja and Valev (2004) are along similar lines. They use GMM dynamic panel techniques on the sample of seventy four countries for the period from 1960 to 1995 in order to find out whether the influence of finance on economic growth depends on the development level of financial system. They split the countries in three groups and find out that in countries with low financial development, additional improvements in the financial markets do not have a clear effect on growth - depending on the financial indi- cators used it is either positive (ratio of commercial bank assets to commercial bank and central bank assets) or nonexistent (share of credit to private sector to GDP). They explain this difference by indicators being better at measuring the size of the financial system, and others efficiency. In countries where financial development has passed a certain threshold (the “middle” region), it exerts a strong positive effect on economic growth. In the “high” region, the growth effect of financial development declines once it reaches very high lev- els. Common characteristic of countries in the “low” region is that they all have a high level of inflation (above a certain threshold), which maybe explains why there is no link between finance and growth. Favara (2003) also finds out that the relationship between fi- nancial development and economic growth is non-linear. The financial sector exerts pos- itive effects on growth only at intermediate levels of financial development.

In the context of the EU, Member States face a fiscal framework that asks for the implementation of sound fiscal policies, notably within the Stability and Growth Pact (SGP) guidelines put forward in 1997. In fact, institutional restrictions to budgetary decision-making are a common feature of fiscal governance in advanced countries (see Hallerberg et al., 2007 for an overview). In addition to excess spending in the absence of such rules, previous literature also suggests that the so-called “common pool problem” may induce a pro-cyclical bias in fiscal policy (Tornell and Lane, 1999). Yet another rational for the implementation of such fiscal rules is to prevent policymakers from exacerbating macroeconomic volatility which is known to be detrimental to output growth. However, the Member States’ track records of effectively implementing fiscal rules have been mixed. 23 Therefore, it is relevant to assess whether such fiscal rules, while aiming at improving fiscal positions, also play a role in fostering growth, particularly when interacted with different levels of government size. To our best knowledge such an empirical exercise has never been conducted.

Several studies in the growth literature have found a negative bivariate relationship between growth and the measure of government size. 10 It is well known that the inclusion of particular control variables in a growth regression can wipe out this bivariate relationship (e.g., Easterly and Rebelo, 1993). Thus, it is necessary to consider which information to include in such growth regressions as control variables. Sala-i-Martin (1997) running two million regressions found 60 variables to be significant in at least one growth regression. In a more robust analysis, Levine and Renelt (1992), applying the Extreme Bound Analysis initially proposed by Leamer (1983), found robust cross-country growth correlates to be: (i) the average investment share of GDP; (ii) the initial log of GDP per capita; (iii) initial human capital; and (iv) the average growth rate of the population. The initial level of GDP is not only a robust and significant variable for growth (in terms

Public spending is widely seen as having an important role in supporting economic growth. On the other hand, a lower level of spending implies that fewer revenues are needed to achieve balanced budgets, which means that lower taxes can be levied, therefore contributing to stimulate growth and employment. Public spending is a key variable that influences the sustainability of public finances via effects on fiscal balances and government debt, and this is relevant for the success of common monetary areas such as the European Monetary Union. Additionally, in the European Union, the so-called Lisbon Agenda also assigned a relevant role to the reform of public finance in order to foster economic growth. For those reasons, a firm control and, where appropriate, reduction of public expenditure is important and a balance has to be drawn between running down public debt, cutting taxes and financing public investment in key areas.

This work tries to assess the impact of government investment in engineering construction, communication technology and transportation on economic growth in Nigeria. One null hypothesis guided the study and data was collected from 1977 to 2008 from Central Bank of Nigeria statistical bulletin. Data were analysed using regression, F and t tests, stationary and co-integration tests. Results revealed that increases in government expenditure in engineering construction impacted more significantly on economic growth than their expenditure on transport and communication. Increased expenditure on all sectors was recommended especially on engineering construction. In addition policy modifications are needed to ensure that government expenditure on the transportation and communication sector achieve greater impacts on economic growth.

Consider a small economy, open to foreign investment and where foreign investors borrow in the international capital market. The interest rate is given by the international interest rate, r = r ∗ and the supply of credit is infinitely elastic. The cost of innovation may be identical between national and foreign investors or may be smaller for foreign investors because they are introducing in our economy a set of new goods that have been developed and produced elsewhere. In any case, there will exist an unique production cost that will be equal to the international one. 3 If a ∗ < a all innovation will end up being done by foreign investors. Assume government allows for tax reduction, d, to foreigners in order to stimulate FDI and thus the innovation rate. The value of the patent, v t , is now given by:

We may interpret these findings as follows. First, if those municipalities, which strongly suffer from seasonal population movements for location specific reasons, as Constância and Ferreira do Zêzere, Rio Maior and Lisbon, finance their services mainly through taxation it may be the case that local residents subsidise the consumption of local services by non-residents. If instead of taxation, local services where mainly financed through user charges the “spill over effect” or the indirect subsidisation element would be reduced (see De Borger et al. (1994) and Cullis and Jones (1998)). Second, we may hypothesise that mobile citizens/consumers tend to move into those communities that have a bundle of services that best match their own preferences (see Tiebout (1956)). Then, we may also argue (see Grossman, Mavros and Wassmer (1999) that Sesimbra, Sintra, Seixal and Oeiras metropolitan municipalities were successful in terms of being perceived by mobile consumers as “effective substitutes” for other communities including central metropolitan city. Additionally, although metropolitan areas face more