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Research and development (R&D) tax credits are widely employed among the OECD countries to promote business sector investments in innovation. The implementation of R&D tax credit schemes, however, varies across countries. The empirical research on the effectiveness of R&D tax incentives suggests that the strength of company responses (in R&D expenditures) to more generous tax incentives substantially differ across countries. We use data from 25 OECD countries, collected from 2010 to 2018, to explore the relationship between a set of R&D tax scheme features and innovation performance. Our estimation results show that the business sector R&D expenditure is higher among those countries that have implemented either an R&D tax credit scheme with an incremental deduction basis or a hybrid scheme with both volume-based and incremental tax relief components. The input additionality is highest when the R&D tax incentives are based on the incremental deduction. Further, the hybrid tax credit scheme positively relates to innovation output. The business sector R&D investment are higher in the countries with an R&D tax credit scheme that provides favorable treatment for SMEs or option to carry forward unclaimed R&D tax credits.

Artikkelissa tutkitaan Suomen yrityssektorin palkanmuodostuksen makrojoustavuutta yksilöaineistoilla. Erityisesti selvitellään sitä, missä määrin niin sanotut liukumat eli sopimuskorotukset ylittävät palkankorotukset ovat toimineet palkanmuodostuksen joustotekijänä suhdanteissa, alueellisissa eroissa ja työntekijöiden välillä. Kiinnitämme erityistä huomiota mittausnäkökohtiin. Mittaamme palkkainflaatiota saman työnantajan samassa tehtävässä jatkaneiden työntekijöiden palkkojen vuosimuutoksella henkilötason palkkarakenneaineistoa käyttäen. Arvioimme, että näin liukuma voidaan mitata tarkemmin kuin virallisista palkkatilastoista, koska työntekijärakenteiden muutokset voidaan ottaa huomioon tarkasti. Havaitsemme, että tässä mitattu liukuma on ollut merkittävä joustotekijä suomalaisessa palkanmuodostuksessa. Tarkastelemme myös tehtävää tai työpaikkaa vaihtaneiden työntekijöiden palkkakehitystä ja havaitsemme niiden joukossa monelta osin samankaltaista dynamiikkaa, mutta joissain määrin vielä vahvemmassa muodossa. Tulokset viittaavat siihen, että viime vuosien vahva työttömyyden lasku ja kokoaikatyöllisyyden kasvu eivät johda niin suureen palkkainflaation uhkaan kuin aikaisempien vuosien tilastotietojen perusteella voi odottaa. peerReviewed

In this work, we rely on unconventional data sources to nowcast the year-on-year growth rate of Finnish indus-trial production, for different industries. As predictors, we use real-time truck traffic volumes measured automatically in different geographical locations around Finland, as well as electricity consumption data. In ad-dition to standard time-series models, we look into the adoption of machine learning techniques to compute the predictions.We find that the use of non-typical data sources such as the volume of truck traffic is beneficial, in terms of predictive power, giving us substantial gains in nowcasting performance compared to an autoregressive model. Moreover, we find that the adoption of machine learning techniques improves substantially the accuracy of our predictions in comparison to standard linear mod-els. While the average nowcasting errors we obtain are higher compared to the current revision errors of the official statistical institute, our nowcasts provide clear signals of the overall trend of the series and of sudden changes in growth.

We study immigrants’ effects on firm-level innovativeness. Managers, innovators, and other employees are considered as separate groups both in firm employment and in local areas. For each, we estimate the effects of foreignness, the share of immigrants in each group, and diversity, while controlling for an extensive set of employment and other firm characteristics. Pooled cross-section estimates suggest that a higher initial share of immigrant innovators is associated with a subsequently higher probability of a product innovation; the reverse holds for process innovation. In other words, product innovation benefits from a wider spectrum of innovator perspectives brought about by foreign influence, while process innovation suffers from it. The estimated effect for product innovation is modestly large but nevertheless indicates that a host of other covariates besides immigration are important for innovation. When measured by a fractionalization index, diversity among innovators does not promote product innovation. However, culturally the closest groups of migrants have a positive effect, when considered independently. Thus, in our interpretation, diversity does offer some benefits, provided that enough cultural homogeneity of the group is retained.

Viimeisten vuosikymmenien aikana kansainvälisessä ekonometrisessa tutkimuskirjallisuudessa on esitetty useita makrotaloudellista tilaa kuvaavien muuttujien informaatiota yhdistäviä lyhyen aikavälin mallinnus- ja ennustemenetelmiä. Näitä ns. nowcasting-menetelmiä on myös onnistuneesti hyödynnetty ja sovellettu Suomen talouden seurantaan. Tässä artikkelissa esittelemme katsauksen monella taholla tehtyyn kehitystyöhön ja näiden hankkeiden yhteydessä saatuihin tuloksiin Suomen aineiston tapauksessa. Suomen taloutta koskevien suhdanneindeksien hyödyntämisen myötä suhdanteiden käännepisteiden määrittäminen on tarkempaa ja käännepisteiden tuottamia taantumajaksoja voidaan vastaavasti ennustaa binäärivastemalleja käyttäen. Suomen Pankin nowcasting-malli mahdollistaa puolestaan uusien tilastojulkistusten uutisarvon analyysin. Tilastokeskuksessa ja Etlassa on vastaavasti hyödynnetty moderneja koneoppimisen menetelmiä, jotta puutteellisesta mikroaineistosta kyetään tuottamaan bruttokansantuotteen pikaestimaatteja aiempaa lyhyemmällä viiveellä. ETLAnowprojektissa hyödynnetään puolestaan mm. uusia Google-hakutilastoja työttömyyden ennustamisessa. peerReviewed

Immigrant entrepreneurship is the subject of a prolific economic literature, as well as a source of wide public debate. This is because the participation of immigrants to the business community can provide a significant contribution to innovation and to market dynamics. This report touches multiple aspects of immigrant entrepreneurship in Finland, looking at the years from 2006 to 2014. I find that while the number of self-employed immigrants has increased dramatically, the entrepreneurial rate has been stable. Moreover, the immigrant self-employment rate is similar to the one of natives. I find that the median earnings of foreign entrepreneurs are lower than the ones of Finnish entrepreneurs, but this is driven by the different industry distribution. Finally, I find an overrepresentation of foreign workers and entrepreneurs in the Helsinki region, while the immigrants’ self-employment rate is higher in poorer areas. I gather multiple evidence pointing toward the fact that difficulties in the job market push foreign residents to self-employment. For example, I find a negative correlation between the employment rate and the foreign share of entrepreneurial inflows, and a strong negative relationship between the employment rate and the immigrant self-employment rate at the regional level.

Finland is characterized by a substantial heterogeneity across its regions. Key economic indicators, such as the GDP per capita and the unemployment rate, vary widely for different areas, with Uusimaa, the region where Helsinki is located, being significantly richer than regions such as Kainuu and Savo. This heterogeneity, however, has not been stable over time. We find that many important indicators, namely the GDP per capita, the unemployment rate and real wages and salaries per employee, have been converging across regions over the years going from 2000 to 2014. Moreover, we examine regional values and attitudes, using surveys from the Finnish Business and Policy Forum, and find that there has been a strong regional convergence in terms of trust in political parties and in the EU. In particular, we find that the trust in these institutions has increased more in regions where there was a more negative attitude toward parties and the EU during the initial years of our analysis. On the other hand, we do not find a significant convergence with respect to the attitude towards immigration.

We adopt a series of shrinkage and factor analytic methodologies to compute nowcasts of the main Finnish turnover indexes, using continuously accumulating firm-level data. We show that the estimates based on large dimensional models provide an accurate and timelier alternative to the ones produced currently by Statistics Finland, even after taking into account data revisions. In particular, we find that the turnovers for the service sector can be estimated with high accuracy five days after the reference month has ended, giving more accurate and faster predictions compared to the first official internal release. For other sectors, the large dimensional models provide a good nowcasting performance, even though there is a timeliness-accuracy trade off. Finally, we propose a factor-based methodology to improve the accuracy of the current flash estimates by imputing part of the data sources, and find that we are able to provide better predictions in a more expedited fashion for all sectors of interest.

We analyze the productivity contribution of firms in the Finnish business sector, using data from 2002 until 2014, and assess the role of the dependency status (i.e. whether they are owned, at least partially, by a mother company) of small and medium enterprises in the manufacturing and services industries, together with the whole private business sector. We find that dependent firms have provided a larger contribution to aggregate productivity growth, compared to the independent ones, regardless of the industry, size class and age groups considered. This result is mainly driven by the better reallocation of labour among dependent companies and by the positive productivity contribution of dependent entrants. Inside the dependent category, the foreign controlled firms contribute more to the aggregate productivity than the other dependent companies due to even more efficient reallocation of labour inputs. Moreover, we find that dependent firms tend to reach their peak productivity earlier than their independent counterparts. Finally, we examine the subgroup of high growing enterprises and find that the positive effect of dependencies on the productivity contribution holds also for this class of firms.

In the last couple of decades, advances in information technology have led to a dramatic increase in the availability of economic data. This doctoral dissertation consists of a collection of articles aimed at the study of various econometric methodologies that allow for the use of large datasets in macroeconomic applications. Chapters 2 and 5 present large dimensional models to nowcast and forecast macroeconomic variables of interests, such as Finnish real output and the binary recession indicator. In particular, in Chapter 2 I use microeconomic data to create timely estimates of the aggregate output indicator of the Finnish economy. In Chapter 5, I use a large dimensional probit model to compute short and long-term forecasts of the United States recession indicator. Chapters 3 and 4 consist of studies related to Finnish enteprises. Specifically, in Chapter 3 I examine the employment behavior of small and large Finnish firms and analyze how their job creation and cyclicality has differed over the last 16 years. In Chapter 4, I analyze the effect of shocks to large Finnish corporations onto the aggregate business cycle, finding that the shocks to a small number of companies are able to explain a substantial share of the fluctuations in aggregate output. Ei saatavilla

We contribute to the extensive literature on the relationship between firm size and job creation, by examining the effects of dependencies between enterprises. Using Finnish monthly data encompassing the population of Finnish private businesses, we calculate the gross job creation and destruction, together with the net job creation, for different size classes and industries. Importantly, we divide firms into a dependent (i.e. owned, at least partially, by a large company) and independent category. Due to the quality of the data, we are able to isolate the 'organic' growth of firms, disregarding the effects of mergers, split-offs and other legal restructuring. We find that independent companies have shown a considerably higher net job creation, regardless of their size class. However, dependent firms do not show particularly different behaviors with respect to the sensitivity to aggregate conditions, compared to their independent counterparts. Once we control for age, we find that independent firms generate more (net) jobs during the early years of their existence but destroy more jobs once they become older.

In this paper, I use a large set of macroeconomic and financial predictors to forecast U.S. recession periods. I adopt Bayesian methodology with shrinkage in the parameters of the probit model for the binary time series tracking the state of the economy. The in-sample and out-of-sample results show that utilizing a large cross-section of indicators yields superior U.S. recession forecasts in comparison to a number of parsimonious benchmark models. Moreover, data rich models with shrinkage manage to beat the forecasts obtained with the factor-augmented probit model employed in past research.

In this paper, we use monthly employment data of Finnish firms to examine the differences in the employment behavior between big and small enterprises. In particular, we investigate which size class of firms has been growing more, which one has been the driver of net job creation and finally which type of enterprise has been more procyclical. In line with previous literature, we utilize various definitions to include a firm inside the small or large category, and consider both one dataset including entry and exit and one including only long-lasting firms. We find that small firms have shown higher growth rates, on average, and that they have been the driver of employment creation. Finally, we find that large firms are more procyclical than small enterprises, especially during economic contractions.