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Jyrki Ali-Yrkkö, Reda Cherif, Fuad Hasanov, Natalia Kuosmanen, and Mika Pajarinen
Do workers hired from superstar tech-firms contribute to better firm performance? To address this question, we analyze the effects of tacit knowledge spillovers from Nokia in the context of a quasi-natural experiment in Finland, the closure of Nokia’s mobile device division in 2014 and the massive labor movement it implied. We apply a two-stage difference-in-differences approach with heterogeneous treatment to estimate the causal effects of hiring former Nokia employees. Our results provide new evidence supporting the positive causal role of former Nokia workers on firm performance. The evidence of the positive spillovers on firms is particularly strong in terms of employment and value added.
Jyrki Ali-Yrkkö, Reda Cherif, Fuad Hasanov, Natalia Kuosmanen, and Mika Pajarinen

used these approaches to explicitly account for the heterogeneous treatment intensity in the context of knowledge spillover effects. 6 The rest of paper is structured as follows. In Section 2, we present the empirical motivation for this study. Section 3 presents an identification strategy and econometric specification used to estimate causal spillover effects. Section 4 describes our data sources. The main empirical results are presented in Section 5. Section 6 presents our concluding remarks. III. Empirical Background The purpose of this section is to

Jyrki Ali-Yrkkö, Reda Cherif, Fuad Hasanov, Natalia Kuosmanen, and Mika Pajarinen

necessarily represent the views of the IMF, its Executive Board, or IMF management. I. ABSTRACT Do workers hired from superstar tech-firms contribute to better firm performance? To address this question, we analyze the effects of tacit knowledge spillovers from Nokia in the context of a quasi-natural experiment in Finland, the closure of Nokia’s mobile device division in 2014 and the massive labor movement it implied. We apply a two-stage difference-in-differences approach with heterogeneous treatment to estimate the causal effects of hiring former Nokia employees. Our

Mr. A. J Hamann
Italy’s pension system was reformed in August 1995. The new system has various desirable long-run properties and, overall, it represents an improvement over earlier systems. However, it fails to address two longstanding problems: extremely high contribution rates, and a lack of provisions for dealing with the substantial deterioration in demographic ratios expected over the next 30-40 years.
Mr. Francesco Caselli and Mr. Philippe Wingender
This paper investigates the heterogenous effects of budget balance rules on fiscal policy in a large sample of countries. To derive country-specific treatment effects of fiscal rules and conduct inference, we use a Synthetic Difference-in-Differences Method. Our results indicate that countries with a budget balance rule improve their fiscal balance on average by around 3 percent after its introduction. However, our results also illustrate the importance of going beyond the average treatment effect, as it masks significant heterogeneity in the country-specific impact of the rule. We find that countries that would have had large deficits in the absence of the fiscal rule exhibit positive treatment effects, thus reducing their budget deficits. On the other hand, countries with budget surpluses respond to fiscal rules by reducing their budget surplus and moving closer to the numerical target of the rule. Our results also suggest that rules’ design matters: a small overall number of fiscal rules, and the presence of a monitoring process outside the government, especially at the supra-national level, improve significantly the effectiveness of the rules.
Mr. A. J Hamann

less heterogeneous treatment of different categories of workers. The new system also represents an improvement over the previous one by being more transparent and by being cast in terms of a clear set of parameters that can be modified without need for a full-fledged reform. Nevertheless, the Dini reform still leaves in place a comparatively generous system of benefits financed by high contribution rates for dependent workers and does not address the problem posed by the demographic transition in prospect during the first half of the next century. Moreover, by

Mr. Andrew J Tiffin
Machine learning tools are well known for their success in prediction. But prediction is not causation, and causal discovery is at the core of most questions concerning economic policy. Recently, however, the literature has focused more on issues of causality. This paper gently introduces some leading work in this area, using a concrete example—assessing the impact of a hypothetical banking crisis on a country’s growth. By enabling consideration of a rich set of potential nonlinearities, and by allowing individually-tailored policy assessments, machine learning can provide an invaluable complement to the skill set of economists within the Fund and beyond.
Mr. Raphael A Espinoza
In this paper, we estimate the aggregate and sectoral fiscal multipliers of EU Structural Investment (ESI) Funds and of public investment at the EU level. We complement these results with a specific application to the case of Slovenia. We first analyze aggregate data and find large and significant multipliers and strong crowding-in of private investment. Our main findings show that positive shocks to ESI Funds are followed by an increase in output that ranges from 1.2 percent on impact, to 1.8 percent after 1 year, and by an increase in private investment between 0.7 and 0.8 percent of GDP. We address country heterogeneity by dividing countries according to key characteristics that have been known to affect multipliers. In particular, we find higher multipliers in a group of CEE countries that are important recipients of European funds and are characterized by fixed exchange rate regimes and sound public investment governance (e.g. Croatia and Slovenia). We also complement the aggregate analysis by estimating the effect of different types of public investment and the effect of public investment on different sectors of the economy.
Sumin Chun, Karmen Naidoo, and Nelson Sobrinho
We construct a high-frequency dataset that combines information on all IMF lending and proxies of monthly economic activity during the first two years of the COVID-19 pandemic (2020–21). Using this novel dataset and standard econometric techniques we find a positive and significant marginal effect of IMF financing on economic activity in low-income countries (LICs) and emerging market economies. We also present tentative evidence that IMF financing may have helped economic outcomes by easing fiscal budget constraints, allowing for larger government spending in response to the pandemic. Overall, this evidence suggests that IMF financing helped lessen the negative impacts of the pandemic on economic activity, especially in LICs.