Inter Regional Effect of Public Debt: A Small DSGE Model of France, Germany and. Italy. Adeel Sultan Kadri Research Associate

Transcription

1 Inter Regional Effect of Public Debt: A Small DSGE Model of France, Germany and Italy Adeel Sultan Kadri Research Associate adeelkadri@hotmail.com Faisal Sultan Qadri Lecturer, Govt. Premier College no.1 faysalsultan@yahoo.com Abstract: The study builds and solves a small, multicounty DSGE model in order to enlighten the empirics of macroeconomic linkages among interdependent economies. It used the dataset from OECD data bank covering the time period of The model revealed that the capital flows from high inflation economies to the economies having moderate level of inflation. It also found that Italian economy is relatively more sensitive to debt shocks from French economy where as German economy is comparatively stable.

2 Introduction: Recent economic crisis in Euro zone has alarmed the governments and the role of fiscal consolidation is now considered crucial in economic stability (Freedman et al. 2009). All across Europe countries like Germany, Greece and France etc. has put down fiscal consolidation plans by cutting public investment, wages and employment. These cuts in public expenditure and increase of VAT and income taxes have short run costs and long run benefits (Nikolai and Thomas 2011). Macro-economic interdependence of euro zone has potentially deep implications. Spillovers of common monetary policy are non-trivial if structual and fiscal policy reforms adapted (Gomes, Jacquinot and Pisani 2011). In order to understand fiscal transmission mechanism and spillover effect of fiscal decisions in Euro zone the study develops a Dynamic Stochastic General Equilibrium (DSGE) model of top three economies of Euro zone 1 i.e. Germany, France and Italy. DSGE model provides a reliable policy tool for evaluating current and alternate policy scenarios. Gali and Monacelli (2008) analyzed optimal monetary and fiscal policy under common monetary union. Bosca et al. (2010, 2009a and 2009b) evolved policy measures by REMS (Rational Expectation Model) model later which was used by Spanish government to analyze the impact of welfare policies on employment. Christiano et al. (2009), Hall (2009) and cogen et al.(2009) analyzed the effect of fiscal multipliers using simulation models. Freedman et al (2009) enlighted the short run benefits and the long run costs of fiscal deficit. Colciago et al. (2009) determined the role of automatic equilibrium under monetary union. Whereas, Coenen et al.(2010a, 2010b) and Hebous (2010) studied a comprehensive effect of fiscal policy through simulation models. 1 United Kindom was not used in top three economies because it doesn t share common currency.

3 These studies reflects the importance of simulation modeling to analyze the effect of fiscal and monetary policy. DSGE modeling is a reliable tool for analyzing the policy scenarios and its implications. Common monetary policy (Euro Zone) possesses many challenges like capital outflow and impact of fiscal debt one economies on other economies. The study is organized in the following sections. Section 2 contains reviews of the selected studies on the subject, section 3 discusses the features and structure of the DSGE model. Section 4 comprises of model solution and analysis whereas section 5 concludes the study. Review of Literature: Afonsa and Soua (2009) analyzed the consequences of fiscal policy on macroeconomic conditions. The study empirically analyzes the effect of fiscal policy on output, stock prices, exchange rate and other macroeconomic variables. It analyzed economies of U.S, Germany, Italy and UK. Quarterly dataset ranging from 1970:3-2007:4, 1980:3-2006:4, 1986:2-2004:4 and 1964:2-2007:4 respectively were used and employed Bayesian structural Vector Autoregressive approach. The authors concluded that government spending shocks lead to important crowding-out effect; has small effect on GDP; have varied effect on housing prices; causes quick fall in stock prices and depreciate effective exchange rate. Whereas, government revenue shocks creates a positive impact on stock prices, housing prices and leads to appreciate effective exchange rate. Bell et al. (2010) frames two fiscal scenarios to inspect how government spending and government revenue interact over changing demographic conditions. Projections of 40 years were formulated

4 introducing modelling innovations with two main scenarios. The author examined the effect of tradeoff between spending categories under constrained fiscal environment. Policy implications highlighted to control debt deficit and if the current policy continues debt spiral fallout would be unsustainable. Perotti (2002) examines effect of fiscal policy on GDP, interest rate and prices. Using quarterly dataset of five OECD countries, the study applied structural Vector Autoregressive approach. It concluded that effect of fiscal policy on GDP is significantly weaker for the last 20 years. Moreover, government spending shocks had significant effect on the real interest rate. Coenen, Strab and Trabandt (2011) investigated how fiscal policy contributed in euro area during great recession. The quarterly dataset from 1985 to 2010 were analyzed and reveals that discretionary fiscal policy have increased GDP growth to 0.5% in recession crisis. Stahler and Thomas (2011) established a Dynamic Stochastic General Equilibrium (DSGE) model to develop fiscal policy simulations. Parallel to existing models of similar nature the study considers two country monetary structures on government expenditure, public investment and public purchases. Authors calibrated the model with Spain and rest of euro zone to simulate different fiscal consolidation scenarios. The study concluded that fiscal consolidation is least damaging if achieved through reduction in wage bill of public sector but most damaging when achieved by reduction in public investment. Kamenik et al. (2013) developed a framework for analyzing fiscal consolidation under different scenarios. The model was applied on Austria, Czech Republic and Germany by developing a

5 baseline scenario assuming future developments. The study concluded that debt targets of Austria and Germany are stable but on the contrary Czech Republic fiscal behavior corresponded to much higher debt target. All countries responded to financial crisis by mixed of short term fiscal expansion and long term austerity. All three countries expect a slowdown in income growth. The study also reveals that Czech and Austria has a risk of debt interest exceeding the nominal income. Cwik (2012) studied the macroeconomic implications of fiscal consolidation ignited by debt brake (balanced budget amendment) in Germany. The accumulation of debt in aftermath of financial crisis and lower fiscal space, the study attempts to analyze it in New Keynesians DSGE model. The study concludes that debt brake invoke fiscal consolidation without constraining policy makers in the time of recession. The study also finds out that debt brake increases multiplier of government spending initially but it adjusts out over time. Fiscal consolidation on government spending and transfers impacts on stabilization of private sector. Hauptmeier, Mittermaire and Rincke (2009) developed a model to characterize taxes and public input. The model uses dataset of 1100 German municipalities from 1998 to A cross sectional two dimension system of taxes and public inputs were developed. The study revealed a positive and significant effect of local business tax rate. It also revealed that local municipalities adjust their spending on infrastructure to average level among neighbour jurisdiction. Afonso and Hauptmeier (2009) examine the fiscal behavior of European countries from 1990 to Responsiveness of budget balances was examined over decentralization, public spending, electoral cycle and government indebtedness. The study concluded that decentralization, public

6 spending and electoral cycle can influence fiscal position. The analysis also reveals that primary balances are highly responsive to government indebtedness. 3. The Model This section presents the structure, main features, variable description and the calibration of model. The model is a multi-country aggregate model for three Euro-Zone economies (France, Germany and Italy). It examines the linkages between public debt and aggregate economy of the interdependent economic region. Dynamic Stochastic General Equilibrium model is an ideal framework for analyzing the simultaneous structural linkages between equations. This frame work was especially developed and very suitable to analyze fiscal policy issues (Stahler and Thomas, 2011). The details of the model are discussed further in the study. 3.1 Structure of the model This is a small model consists of 12 equations out of which 09 are structural equations while 03 are identities. The first three equations represents demand block, next three equations formulates supply block and the last three equations represents investment block explicitly inorder to enlighten the intercountry linkages between these three countries.the model consists of 24 variables in total,out of which 12 are endogenous while 12 are exogenous variables 2. The block wise description of the model is discussed in the next section. 2 The variable description is presented in the appendix 1. data source: OECD data bank.

7 3.1.1 Demand block The demand block is comprised of three equations representing the aggregate demand in France, Germany and Italy respectively. Among the other theoretically acceptable specifications, the finally selected set of variables have the maximum explanatory power and overall statistical significance without ignoring the empirics of macro modeling studies for the economically interdependent regions. Equation 1 Fgdpdef = *Fdebtpgdp*Fgdp *Fint * Foutputgap(-1) (0.000) (0.041) (0.045) Adjusted R D. W Statistics 1.387Probability(F-statistics) The aggregate demand in all the three countries is modeled under price adjustment mechanism. In case of France, the statistically fittest combination shows the positive and statistically significant role of public debt and nominal interest rate in the determination of general price level. Partial adjustment mechanism of output gap also found to be a significant factor in the determination of price level of France. Equation 2 Ggdpdef = *Gdebtpgdp*Ggdp *Gint *Fgdpdef *Igdpdef (0.010) (0.002)(0.000) (0.060) Adjusted R D. W Statistics 1.967Probability(F-statistics) In case of Germany, the initial two variables are same. The sign of interest rate coefficient is negative that shows the effectiveness of monetary policy in controlling general price level. Interestingly, the Germany s price level is found to be positively affected with France s GDP deflator and negatively affected with Italy s GDP deflator. In case of Italy, the all variables are same as in the equation 2. Equation 3 Igdpdef = *Idebtpgdp*Igdp * Iint * Ioutputgap(-1) *Fgdpdef (0.008) (0.000) (0.000) (0.000) Adjusted R D. W Statistics 1.512Probability(F-statistics) 0.000

8 3.1.2 Supply block Supply block is modeled through classical production function and growth equations. In case of France, Germany and Italy, labor and capital both found to have positive and significant role in determining GDP. Equation 4 Fgdp = *Flabour Fgfcf (0.000) (0.000) Adjusted R D. W Statistics 1.249Probability(F-statistics) Equation 5 Ggdp = *Glabour *Gfcf (0.051) (0.000) Adjusted R D. W Statistics 1.147Probability(F-statistics) Equation 6 Igdp = *Ilabour *Igfcf (0.000) (0.000) Adjusted R D. W Statistics 1.274Probability(F-statistics) Investment block This block connects the demand and supply at aggregate level. This is especially important because it links the investment with real interest rate. In case of Italy and Germany the investment seems to be independent of real interest rate and significantly linked with the GDP as explained by Keynesian macroeconomic framework. Equation 7 Fgfcf = *FINT-FINF (0.015) Adjusted R D. W Statistics Probability(F-statistics) Equation 8 Ggfcf = *Ggdp (0.007) Adjusted R D. W Statistics Probability(F-statistics) Equation 9 Igfcf = *Igdp (0.000) Adjusted R D. W Statistics Probability(F-statistics) 0.000

9 3.2 Main features of the model The model is different from the other models available for analyzing the fiscal sector dynamics. In a simple and aggregated manner, the model analyses inter-country linkages between France, Germany and Italy without modeling the trade and international financial flows. It explicitly focuses the impact of a change in monetary and fiscal variable/s on the domestic economy and the region through a change in the price level, real interest rate and finally the investment flows. This model does not only consider the domestic determinants of aggregate demand, aggregate supply and the domestic investment but also included the inter-regional factors which contribute in the determination of aggregate macroeconomic indicators in a economically integrated region. 3.3 Model calibration Model is calibrated by employing ordinary least square method after evaluating the time series properties of data. The coefficient of behavioral equations represents the long run responses of the variables estimated through Engel Granger two step procedures. The obtained coefficients are then fine tuned in such a manner that it reproduced the deterministic historical trends in the data with remarkable accuracy. 3.4 Within sample forecast Before establishing the baseline for scenario analysis, it is necessary to evaluate the model s performance with in the sample period. First, the within sample performance is evaluated through deterministic and static model.

10 Within sample forecast in deterministic and static model The model is found to replicate history with reasonable accuracy and is fit for further evaluation process. The next step is to evaluate the performance of the model under deterministic and dynamic model. The figure of this test is presentd below.

11 Within sample forecast in deterministic and dynamic model The model is found to have satisfactory performance in reproducing the historical trends of all variables with no exceptions. The real world economic factors are stochastic in nature in most of the cases. Therefore, it is necessary to check the model performance in stochastic and static frame work. The model is tested again and the obtained graphs are presented below.

12 Within sample forecast in stochastic and static model Again, the model successfully reproduces the historical trends in the endogenous variables. Finally, the model is tested under the stochastic and dynamic way in order to evaluate its ability to determine a reasonably reliable baseline for the analysis. The model is tested again and the resulting graphs are presented below.

13 Within sample forecast in stochastic and dynamic model The graphs show that the model is fit to produce a reliable baseline for scenario analysis. 3.5Baseline simulation For baseline simulation, the values of exogenous variables are estimated systematically. In case of labor force, it is estimated through dynamic forecast of AR (1) series having reasonable forecast accuracy. Output gap is generated by applying the average growth rate of the overall sample period in case of France. The same series is generated in case of Germany and Italy by applying the average growth rate of the last 09 and 12 years respectively. This period is selected because of the

14 existence of extreme values in the 10 th and 13 th year respectively.. Interest rate is assumed to be constant at the annual Euribor value for Public debt as percentage of GDP is assumed to be constant at last 05 year s average for all the three countries. The baseline Baseline simulation

15 3.6 Scenarios Finally three scenarios are evaluated in order to see whether the public debt of one country can affect the macro economy of the other interdependent economy or not? If it can affect, then to what extent? Scenario 1 The scenario 1 assumes an Increase in debt to GDP ratio of France by0 2% per year from 81% to 91% of GDP from 2013 to This is very likely situation as per the historical trend of France. The result of this situation is presented in the graphs below. This shock would affect French GDP deflator which would increase 5.6 percent as compared to the baseline. The process continues with increasing rate and deflator increases by 10 percent as

16 compared to the baseline in the fifth year. Growth in deflator pushes the output as well as input prices upwards. This situation results in a capital outflow from high inflation economy to the economy with moderate level of inflation. The graph shows that investment in Germany increased in the situation which indicates the capital inflow from relatively high inflation economy. This shock would gradually decrease the GDP of France with increasing magnitude from baseline. GDP would decrease from baseline in the first year (2013) to 1.48 percent in the fifth year (2017). This shock ultimately transmits its effect to the region and Italian GDP would start decreasing though with decreasing rate. It would decrease the GDP as compared to the baseline by 0.72 percent in 2013 to 0.35 percent in In case of Germany, GDP would decrease initially by 0.12 percent, then start increasing and finally it would decrease by 0.10 percent in Scenario 2 The scenario 2 assumes an Increase in debt to GDP ratio of France by 2 % per year from 81% to 91% of GDP and monetary tightening by ECB resulting in an increase in interest rate by 0.2% per year from 0.7% in 2013 to 1.5 from in This is also a likely response of ECB in order to keep price stability in the region as it was done in the past.

17 The results shown a decline in GDP in France, Germany and Italy by 0.71 percent, 0.04 percent and 9.75 respectively. This shows Italian economy s vulnerability and German economy s strength to the French fiscal shock accompanied by a monetary tightening, Scenario 3 In the most likely case expected due to historical trends,, the scenario assumes an increase in debt to GDP ratio of France, Germany and Italy by 2 %, 2% and 3% per year respectively accompanied by monetary tightening resulting an increase in interest rate by 0.2% per year from 0.7% in 2013 to 1.5 from in 2017.

18 The results show that the shock would decrease the GDP by increasing magnitude. As compared with the baseline, GDP falls by 0.69 percent in 2013 to 1.64 percent in The results show that the German economy faces a capital inflow because of relatively high inflation in the other two economies and German GDP would rise irrespective of the same action by the two other governments.

19 Conclusion The study builds and solves a small, multi-country aggregate model for three Euro-zone economies (France, Germany and Italy) analyses the effects of public debt on aggregate economy of the interdependent economic region. The model analyses inter-country macroeconomic linkages between France, Germany and Italy without modeling the trade and international financial flows. It explicitly focuses the impact of a change in monetary and fiscal variable/s on the domestic economy and the region through a change in the price level, real interest rate and finally the investment flows. The study found the evidences of capital outflow from high inflation economy to the economies having moderate level of inflation. The study also found that Italian economy is relatively sensitive to the debt shocks from French economy whereas German economy is less sensitive to the same accompanied by a monetary tightening. In this situation, the major Eurozone economies should contain the public debts and keep the inflation at a reasonably low level without relying much on monetary tightening.

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21 GOMES, S., P. JACQUINOT AND M. PISANI [2010], The EAGLE: A Model for Policy Analysis of Macroeconomic Interdependence in the Euro Area, European Central Bank, Working Paper, No. 1195, Frankfurt am Main. GALÍ, J. AND T. MONACELLI [2008], Optimal Monetary and Fiscal Policy in a Currency Union, Journal of International Economics, 76, HALL, R. E. [2009], By How Much Does GDP Rise if the Government Buys More Output?, National Bureau of Economic Research (NBER), Working Paper, No , Cambridge, MA. HAUPTEMIER, S., F. MITTERMAIER and J. RINKE (2008), Fiscal Competition over Taxes and Public Inputs: Theory and Evidence, Cesifo Working Paper, No HEBOUS, S. [2010], The Effects of Discretionary Fiscal Policy on Macroeconomic Aggregates:A Reappraisal, Journal of Economic Surveys, forthcoming. KAMENIK, O. et al. (2013), A Simple Fiscal Stress Testing Model: Case Studies of Austrian, Czech and German Economies, OECD Economics Department Working Papers, No. 1074, PEROTTI, R. (2004): "Estimating the Effects of Fiscal Policy in OECD Countries" Working Papers 276,IGIER. STAHLER, N. and THOMAS, C. (2011).FiMod - A DSGE model for fiscal policy simulations. Discussion Paper Series 1: Economic Studies 2011,06, Deutsche Bundesbank, Research Centre. Appendix 1 Variable Fgdp Fgdpdef Fgfcf Ggdp Ggdpdef Ggfcf Igdp Igdpdef Igfcf Attribute GDP (France) GDP deflator (France) Investment (France) GDP (Germany) GDP deflator (Germany) Investment (Germany) GDP (Italy) GDP deflator (Italy) Investment (Italy)

22 Finf Ginf Iinf Fint Gint Iint Flabour Glabour Ilabour Foutputgap Goutputgap Ioutputgap Frealint Grealint Irealint Fdebtpgdp Gdebtpgdp Idebtpgdp Inflation (France) Inflation (Germany) Inflation (Italy) Nominal interest rate (France) Nominal interest rate (Germany) Nominal interest rate (Italy) Labour force (France) Labour force (Germany) Labour force (Italy) Output gap (France) Output gap (Germany) Output gap (Italy) Real interest rate (France) Real interest rate (Germany) Real interest rate (Italy) Public debt as percentage of GDP (France) Public debt as percentage of GDP (Germany) Public debt as percentage of GDP (Italy)