The economic divergence between the South and the North of Italy is widely recognized and is known as `Italian dualism'. Since the aftermath of World War II, the macroeconomic indicators of the two Italian areas -notably, the GDP, the private investment, the export and the employment rate- show a jumpy process of convergence/divergence. The recent era of economic stagnation and the economic downturn following the Global Financial Crisis have emphasized the economic gap between the two Italian areas. Currently, the South of Italy has one of the highest levels of material deprivation in Europe, whereas the North has one of the lowest (OECD, 2019). Despite the relevance of the issue, the recent macroeconomic literature offers only a few and shyly attempts that address the understanding and the policy consequences of the Italian dualism. For instance, while the 80% of both EU and national resources for economic and social rebalancing actions are currently devoted to Italian southern regions, the policy-benchmark on the effects of fiscal policy relies exclusively on national fiscal multipliers. One of the reason behind the lack of a consolidated evidence is that local-level time series are limited, short and have a too low frequency. This project aims at filling this gap by offering the opportunity to build a unique dataset and to explore the subject matter in several ways. First, by exploiting a source of regional data from SVIMEZ, the project aims at rebuilding regional time series from 1945 to 2020. Second, by implementing mixed-frequency techniques the regional series will move from the annual to the quarterly frequency. Third, the new dataset will be employed to estimate a structural macroeconomic model for Italian regions accounting for regional heterogeneity in the development process. Therefore, the ultimate goal will be to use this framework to shed a new light on the effectiveness of fiscal policy in the Italian regions.
The work aims at enhancing the existing literature in several aspects: i) it engages to build a unique dataset of regional macroeconomic time series from 1945 to 2020; ii) it attempts to move the frequency of these series from yearly to quarterly by exploiting mixed-frequency techniques; iii) it build a regional Panel VAR comprising of all Italian region which, at the same time, accommodates macro area heterogeneity to emerge from a more data-rich environment; iv) it proposes a new identification method to disentangle the contribution of different kinds of fiscal shocks by means of sign restrictions by extending the evidence on regional multipliers and the effects of fiscal policy in Italy.
With goals i) and ii) this project will improve the reliability of regional estimates and forecasts. Notwithstanding, it will provide a fair ground to implement nowcasting of regional GDPs, which is almost absent in Italy. The main issue is that official data for many key macroeconomic regional variables are released with a significant delay and only at annual frequency. Nowadays, the last current figure available for Italian regional GDP is 2019 while the oldest one dates back to 1995. While the availability of a deep dataset from SVIMEZ will allow re-building the macro history of Italian regions, the mixed-frequency econometrics will allow to implement simple Bayesian techniques to produce prompt estimates of regional macro variables. Yet, these achievement will provide both national and local policymakers with a more soundly framework to study the effects of local fiscal policy.
With goals iii) and iv) the project will enhance the empirical evidence on the effectiveness of Italian fiscal policy. In particular, the project aims at disentangling current expenses, taxes and public investment measures. The latter will be also disaggregated in sub-components and studied in details. To retrieve the information related to government expenditure on specific public services (e.g health, education, ecological transition), we will refer to 'Regional Public Accounts' (Conti Pubblici Territoriali, CPT) available by the Department for Development and Cohesion Policies of the Italian Ministry of Economy and Finance. The potential of this dataset lies on the availability of the series of capital account public expenditure disaggregated by regions, levels of government and policy intervention measures. The degree of disaggregation allows to conduct provide policymakers with a more accurate analysis, without omitting important different types of capital expenditures.
O. Blanchard and R. Perotti. An empirical characterization of the dynamic effects of changes in government spending and taxes on output. The Quarterly Journal of Economics, 117(4):1329-1368, 2002.
E. Marrocu and R. Paci. The effects of public capital on the productivity of the italian regions. Applied Economics, 42(8):989-1002, 2010.
G. Koop and D. Korobilis. Forecasting with high-dimensional panel vars. Oxford Bulletin of Economics and Statistics, 81(5):937-959, 2019.
G. Koop, S. McIntyre, J. Mitchell, and A. Poon. Regional output growth in the United Kingdom: more timely and higher frequency estimates from 1970. Journal of Applied Econometrics, 35(2):176-197, 2020.