Mindaugas Butkus (p)

Previous studies that apply the conditional beta-convergence model to examine outcomes of the Cohesion Policy augment the specification with Cohesion payments or eligibility status as a growth factor. Some specifications interact Cohesion Policy variable with factors that are considered as mediating growth outcomes of the Cohesion Policy. Research that interacts Cohesion Policy with the initial level of development (Rodriguez-Pose and Novak, 2013; Pellegrini et al., 2013; Pinho et al., 2015) uses this multiplicative term to examine how the level of development mediates the effect that Cohesion Policy has on growth. Surprisingly no research interprets this multiplicative term in a way to examine how Cohesion Policy mediates the relationship between the initial level of development and growth, i.e. regional convergence. Furthermore, no research interacts Cohesion Policy, the initial level of development and institutional quality to examine mediating effects of the Cohesion Policy, institutional quality and their interaction on convergence. Moreover, research that uses model specifications with interaction between interval/ratio variables term rarely (except for Pinho, 2015 and Rodriguez-Pose and Garcilazo, 2015) recognizes that estimated marginal effect (slope coefficient), as well as its significance, is conditional, i.e. depends on the value of the mediating factor and there could be a range of values for the mediating factor over which the estimated marginal effect of Cohesion Policy is positive and the range over which this effect is negative. The same considering the significance of the estimated marginal effect of the Cohesion Policy.
This presentation aims to contribute to the existing literature on the Cohesion Policy outcomes by extending conditional beta-convergence model with a 3-way multiplicative term to examine mediating effects of Cohesion Policy, institutional quality and their interaction on regional convergence.
See further an extended abstract
References:
1. Rodríguez-Pose A, Novak K (2013) Learning processes and economic returns in European Cohesion Policy. Investigaciones Regionales 25: 7–26.
2. Pellegrini G, Busillo T, Muccigrosso T, Tarola O, Terribile F (2013) Measuring the Impact of the European Regional Policy on Economic Growth: a Regression Discontinuity Design Approach. Papers in Regional Science 92: 217–233.
3. Pihno C, Varum C, Antunes M (2015b) Under What Conditions Do Structural Funds Play a Significant Role in European Regional Economic Growth? Some Evidence from Recent Panel Data. Journal of Economic Issues 49(3): 749–771.
4. Rodríguez-Pose A, Garcilazo E (2015) Quality of Government and the Returns of Investment: Examining the Impact of Cohesion Expenditure in European Regions. Regional Studies 49: 1274–1290.

Jan Kluge (p)

The economic catching-up process of poorer regions and the establishment of more even living conditions across Europe are among the main targets of EU policy making. Hundreds of billions of Euros have been spent by the European structural and investment funds during the programme period 2014-2020. Even though there is obvious evidence that poorer regions grow faster than richer ones, it is neither clear whether this is indeed due to the EU’s efforts, nor do we know much about the channels through which poorer regions can speed up GDP growth, let alone the spatial patterns involved. After all, higher growth rates in the new member states could be a mere neoclassical convergence phenomenon rather than a success story of EU regional policy.

In this paper, we aim at identifying the determinants of regional cohesion using state-of-the-art machine learning techniques. First, we estimate the extent to which NUTS 2 regions have truly outperformed their growth expectations using shift-share analysis. Second, we want to attribute this outperformance to the various indicators from the European regional competitiveness index. Due to the "open-endedness" of economic growth models, we can not lean on (or even test) any theoretical underpinning but simply let the data speak in order to find the variables that are best suited to predict regional GDP growth. The method of choice will be Bayesian Additive Regression Trees (BART; see Chipman et al. (2010)) which is a non-parametric approach designed, i. a., for model selection purposes with ex ante unknown regression functions.

Even though this exercise can not make the attempt to assess the causal impact of European regional policy, it can provide insights into the variables (i. e. infrastructure, education, innovation etc.) that are important for economic cohesion. It can therefore give hints about where EU money should go during the programme periods yet to come in order to effectively accelerate convergence.

Alma Mačiulytė-Šniukienė (p)

Large disparities still exist between regions of the European Union, despite the fact that huge Cohesion investments are directed to address this issue. In order to adjust the Cohesion Policy (CP), researchers assess the returns of the CP, but almost all studies are carried out at NUTS1 and NUTS2 or at a country level, despite the fact that major disparities occur at NUTS3 level. Moreover, just a few studies examine the non-linear effects of the CP and none of them cover NUTS3 disaggregation level. To fill the gap of previous contributions, we aim to examine convergence outcomes of the CP at NUTS2 and NUTS3 level and provide main guidelines for adjustment of the EU’s CP. This paper also examines whether EU structural funds support impact heterogeneity depend on institutional quality (IQ) and effects of SF support intensity. Our estimation strategy is based on the modified specification of the difference-in-differences estimator that has an advantage while examining policy effects, using non-experimental data. Empirical applications are based on data over 2000-2006 and 2007-2017 programming period. We found that marginal effect of the CP is diminishing and convergence outcomes depend on institutional quality. The positive returns from SF are higher in regions where IQ is higher. On the basis of research findings, the essential guidelines for the improvement of the CP can be drawn up: i) the distribution policy of Cohesion investments should focus on smaller territorial units in order to reduce disparities at NUTS3 level; ii) the intensity of the CP’s transfers has to be optimized because excessive intensity does not provide positive return.

Kristina Matuzeviciute (p)

The paper contributes to the existing literature on the Cohesion Policy outcomes by extending conditional beta-convergence model with a 3-way multiplicative term to examine mediating effects of Cohesion Policy, institutional quality and their interaction on regional convergence. The empirical analysis based on conditional slope coefficients and conditional standard errors provides evidence that both mediating factors under consideration contribute positively to boosting regional convergence in the EU at NUTS 2&3 disaggregation level but with much bigger success over 2007-2013 programming period compared to the previous one. Moreover, Cohesion Policy and institutional quality act as substituting rather than complementary mediating factors.

Diana Cibulskiene (p), Mindaugas Butkus, Lina Garsviene, Janina Seputiene

The recent economic crisis has led to an unprecedented increase in public debt, though recovery has remained sluggish, raising serious concerns about the public debt impact on economic growth. A growing body of research supports the idea of non-linear debt-growth relationship and estimates the threshold level above which debt has a negative effect on output. The impact of debt on growth depends on the range of factors, therefore recent research has focused on identifying the mechanism of how and under which conditions public debt levels can affect economic growth. However, there is a lack of such studies, as only a few factors and mainly institutional quality are examined as shaping the impact of debt on growth. There are diverse channels through which public debt can potentially have an impact on economic growth. There has been extensive debate in the literature on the question of how government debt affects the size of the fiscal multiplier. There is a lack of discussion on how fiscal multiplier can shape the impact of public debt on economic growth. This research contributes to the scarce literature on the heterogeneous debt-growth relationship and rises the assumption that the factors determining the size of expenditure multiplier are also shaping the impact of the public debt on growth. Since the size of the fiscal multiplier is unknown at a certain point in time and its measurement is tricky it does not provide any practical insights for fiscal policy. First, this study aims to provide a theoretical background on the mechanism of how fiscal multiplier influences the public debt – growth relationship. The second aim is to provide insights on which statistical indicators may signal a low fiscal multiplier, and what values of these indicators may raise the risk of the economic growth-inhibiting effect of public debt.
The empirical examination is based on cluster and comparative analysis of panel data aiming to find periods and groups of countries that are similar in terms of statistical indicators that may signal about the size of the fiscal multiplier. Comparison of the period- and group-specific growth rates allowed to shed some light on the channels and conditions that affect heterogeneity of debt-growth relationship.
Results are in line with those which confirm debt threshold dependence on institutional quality. It is concluded that high levels of public debt not necessarily trigger growth if conditions related to high level of the fiscal multiplier are met.