In many OECD countries, economic growth has yet to recover the lost ground suffered in the aftermath of the financial crisis. In some of them, unemployment has been persistently high, investment rates disappoint, and productivity is extremely sluggish – a “low growth trap”. Put differently, all three sources of sustainable long-run growth under-perform. This jeopardizes societies’ ability “to make good on its promises to current and future generations – to create jobs and develop career paths for young people, to pay for health and pension commitments to old people”. (OECD, 2016). While this partly reflects the persistent weakness of demand in some cases (Mann, 2016), there are policy tools available that affect the long-run productive capacity of the economy, or potential growth.
The macro-econometric approach seeks to relate policy changes to macro-econometric outcomes using econometric estimation methods. The OECD has been heavily relying on this approach. For instance, Égert and Gal (2016) study how various product and labour market policies and regulations affect per capita income growth over different horizons and through the three supply-side channels: multi-factor productivity (MFP), capital deepening and employment.
The macro-econometric approach has been criticised on the grounds that DSGE models would be better suited for the quantification of structural reforms. Yet the appeal of DSGE models to properly take general equilibrium effects into account is to some extent overshadowed by a number of problems. First, DSGE models appear to model the adjustment path to the steady state rather than changes in the steady state due to structural reforms. Second, the way how DSGE models incorporate real world policy changes is often problematic.
There are two classes of DSGE models aimed at analysing the impact of structural reforms on economic outcomes. In the first class of models, competition is captured via mark-ups: lower (higher) mark-ups reflect more (less) intense competition. In these models, mark-ups are exogenous (see e.g. Roeger et al., 2008, 2009, 2010; European Commission 2016). Measuring mark-ups empirically is a notoriously difficult task because they have to be estimated based on complex procedures. These models usually link empirically mark-ups to product market regulation. How this link is established is far from being perfect: only a bivariate relationship between mark-ups and a measure of regulation indicator are used. This means such effects are not conditional on other policies.
In the second class of models, competition is measured through mark-ups, which are endogenous to the model: they depend on the number of competitors, which in turn is a function of entry costs (see e.g. Cacciatore et al., 2012 and 2016). Measuring entry costs empirically is easier because they can be observed directly. For instance, the OECD’s PMR indicator has a sub-component that measures general and sector-specific entry barriers. The World Bank’s Doing Business indicators also provide direct measures of economy-wide entry costs (such as the costs of starting a business). Yet these models do not use actual changes in entry costs. Instead, two commonly used scenarios are based on a unit change in entry barriers or assume a convergence scenario across countries.
The objective of this project would be to better link, compare and reconcile the macro-econometric approach with various types of DSGE models. The project would have five modules:
- Stocktaking of the literature regarding major methodological and modelling choices and results:
- The main features of macro-econometric models of structural reforms
- The main features of the various classes of DSGE model
- Analysing how structural reforms are channelled into DSGE models.
- Looking at measuring mark-ups and entry costs
- Looking at ways of how structural reforms could be better incorporated into DSGE models, in particular those based on exogenous mark-ups. The objective would be to assess in a more comprehensive way the empirical relationships based on which policies are incorporated into the models
- Analysing the effects of DSGE models looking at short-run and long-run effects
- A throughout comparison of the results obtained using the very same structural (product and labour market) reforms in the different macro-econometric and DSGE approaches
- Reconciling the macro-econometric and DSGE models by injecting into DSGE models shocks to MFP, the capital stock and employment due to policy reforms estimated in macro-econometric models.
Cacciatore, M., R. Duval and G. Fiori (2012) “Short-Term Gain or Pain? A DSGE Model-Based Analysis of the Short-Term Effects of Structural Reforms in Labour and Product Markets”, OECD Economics Department Working Papers, No.984, OECD Publishing, Paris.
Cacciatore, M., R. Duval, G. Fiori and F. Ghironi (2016) “Market reforms in the time of imbalance”, Journal of Economic Dynamics & Control 72(2016) 69-93
Égert, B. and P. Gal (2016), “The quantification of structural reforms in OECD countries: a new framework”, OECD Economics Department Working Papers, No. 1354, OECD Publishing, Paris.
European Commission (2016) “The Economic Impact of Selected Structural Reform Measures in Italy, France, Spain and Portugal”, European Institutional Papers no. 23
Mann, C. L. (2016), “Deploy effective fiscal initiatives and promote inclusive trade policies to escape from the low-growth trap” ECOSCOPE, November 28.OECD (2016), “Economic Outlook”, Vol 2016(1)
Roeger W., J. Varga, J. in’t Veld (2008), “Structural reforms in the EU: a simulation-based analysis using the QUEST model with endogenous growth”, European Economy Economic Papers, No . 351.
Roeger W., J. Varga, J. in’t Veld (2009), “Modelling the Lisbon Strategy: Analysing policies to promote knowledge investment with an endogenous growth model", Comparative Economic Studies, No. 51, 520-539.
Roeger W., J. Varga, J. in’t Veld (2010), "How to close the productivity gap between the US and Europe: A quantitative assessment using a semi-endogenous growth model", European Economy Economic Papers, No. 399.