Browsing by Subject "General track"

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  • Jämsä, Pentti (Helsingin yliopisto, 2021)
    The purpose of the thesis is to explore the link between labour markets and transportation accessibility. Accessibility has been estimated with logsum and travel times of public and private transportation. Logsum as a concept has been used in the transportation system estimation, all though all in all logsum as a measure of accessibility is not as established as travel times. This way the overview of the effects of accessibility to employment is thorough. I also evaluate how impact assessment of transportation is done historically and how wider economic impacts are considered in the framework. Cost-benefit analysis is widely used, but the framework should be improved on how to include wider economic impacts. The methods section goes through how transportation system estimation is done. The used data in the estimation is collected from three dependencies. These are the interview-based traveling habits from Helsingin Seudun Liikenne, Statistics Finland metropolitan regional employment statistics and travel times of public and private transportation from Helsinki Region Travel Time Matrix. In the results I go through the empirical model. Travel time, logsum and employment are all viewed as an elasticity measure. The results of the model are reasonable and in line with the previous literature, but the coefficient of determination ends up quite low. This means that the results still need confirmation, either through better data or better estimation model. My results can be viewed as a preliminary result on the link between employment and accessibility.
  • Kuokka, Karri (Helsingin yliopisto, 2021)
    Hinnoittelualgoritmien käyttö on yleistynyt viimeisen vuosikymmenien aikana. Tähän on vaikuttanut erityisesti sähköisten markkinapaikkojen eli verkkokauppojen suosion kasvu. Lisäksi algoritmeihin liittyvä teknologia on kehittynyt ja hinnoittelualgoritmeihin liittyviä palveluita on yhä helpommin yritysten saatavilla. Tässä tutkielmassa tarkastellaan hinnoittelupäätöksissä käytettävien algoritmien vaikutuksia markkinakäyttäytymiseen, missä useat yritykset koordinoivat toimiaan saadakseen kilpailullista markkinatilannetta korkeampia voittoja. Tällainen yritysten välinen kilpailun vastainen yhteistyö, eli kolluusio, on usein kuluttajien ja kilpailun kannalta haitallista. Siksi myös hinnoittelualgoritmien käytön vaikutuksia kolluusion on syytä tarkastella. Tämän tutkielman tavoitteena on tarkastella hinnoittelualgoritmien vaikutuksia erityisesti hiljaiseen kolluusioon. Tarkastelun kohteena on myös se, kykenevätkö tekoälyyn perustuvat algoritmit kolluusion autonomisesti eli täysin ilman ihmisten ohjausta. Tutkielman kirjallisuuskatsauksessa syvennytään tekoälyyn perustuviin algoritmeihin ja hiljaiseen kolluusioon teoriatasolla. Hinnoittelualgoritmien vaikutuksia hiljaiseen kolluusion on vaikea tutkia empiirisin menetelmin, koska hiljaista kolluusiota voi olla vaikeaa havaita markkinoilta ja yritykset harvoin paljastavat hinnoittelussaan käyttämiään algoritmeja. Tästä syystä tutkielman toisena tutkimusmenetelmänä on kokeellinen tietokonesimulaatio, jonka avulla tarkastellaan hinnoittelualgoritmien vaikutuksia hiljaiseen kolluusion. Simulaation avulla pyritään kokeellisesti selvittämään, kykenevätkö tekoälyyn perustuvat hinnoittelualgoritmit kolluusioon autonomisesti. Tutkielman tulosten mukaan hinnoittelualgoritmien käytöllä voi olla vaikutuksia hiljaiseen kolluusioon. Hinnoittelualgoritmien käyttö voi muuttaa markkinarakenteita vaikuttaen hiljaiseen kolluusioon. Vaikutukset markkinarakenteisiin ovat kuitenkin hieman epäselvät ja vaikutukset hiljaiseen kolluusioon voivat olla joko lisääviä tai vähentäviä. Lisäksi hinnoittelualgoritmit voivat toimia myös välillisesti hiljaisen kolluusion fasilitaattorina. Tutkielman tuloksista erityisen mielenkiintoinen on tekoälyyn perustuvien hinnoittelualgoritmien kyky oppia kolluusio autonomisesti. Tätä tulosta tuki aiempaan kirjallisuuteen perustuva kirjallisuuskatsaus sekä tässä tutkielmassa toteutettu tietokonesimulaatio. Yleistyvä hinnoittelualgoritmien käyttö ja niiden kehittyminen voivat aiheuttaa täysin uudenlaisia ongelmia kilpailun tehokkuuden turvaamisessa ja sääntelyssä. Kokeelliseen tutkimukseen perustuvien tuloksien mukaan tekoälyyn perustuvat algoritmit näyttäisivät kykenevän autonomisesti kolluusioon. Jatkossa tutkimusta hinnoittelualgoritmien vaikutuksista kolluusioon olisi syytä laajentaa. Haasteeksi voi kuitenkin muodostua se, miten tutkimusta voidaan toteuttaa sellaisessa taloudellisessa ympäristössä, joka vastaa riittävän tarkasti todellista markkinatilannetta.
  • Kanervo, Atte Jonatan (Helsingin yliopisto, 2021)
    This thesis investigates the tax base and allocation choices in international corporate income tax architecture and provides an evaluation of the effects of the choices made in three different systems: the current system, residual profit allocation, and OECD Pillar One. International corporate income tax design has a significant effect on the functioning of the international economy and on the welfare of individuals. Thus, making the correct design choices is extremely important. This thesis argues that the international corporate income tax system should be designed following certain important principles of taxation: 1) fairness, 2) economic efficiency, 3) robustness to avoidance, 4) administrative ease, and 5) incentive compatibility. The different systems are then introduced in turn and evaluated against these criteria. The thesis finds that the current system suffers from certain conceptual weaknesses that leave significant room for improvement with regards to the set criteria. It is further argued that a reform is required for the continued functioning of the international system. Such a reform could be introduced in the form of residual profit allocation. OECD Pillar One proposal involves elements of residual profit allocation, but in comparing the different systems with each other, this thesis argues that the OECD proposal is too narrow in scope to gain the full benefits of a residual profit allocation system.
  • Kurppa, Sara (Helsingin yliopisto, 2021)
    Työvoiman riittävyys on yksi tulevaisuuden suurimmista poliittisista kysymyksistä länsimaissa. Tähän pyritään löytämään ratkaisuja muun muassa pidentämällä nykyisten työntekijöiden työuria, kuitenkaan lisäämättä työkyvyttömyyseläkkeiden aiheuttamia kustannuksia. Yhtenä mahdollisena ratkaisuna pidetään ammatillisen kuntoutuksen tarjoamia työhön paluu mahdollisuuksia työkokeilun tai uudelleen kouluttautumisen avulla terveydentilalle sopivampaan ammattiin. Tutkimuksen alussa käydään tarkemmin läpi ammatillista kuntoutusta, sen prosessia, kohderyhmää sekä mahdollisia kuntoutuskeinoja. Tavoitteena on selvittää henkilötasoisten muuttujien vaikutusta ammatilliseen kuntoutukseen osallistumiseen. Lisäksi on tarkoitus selvittää, onko osallistumista mahdollista ennustaa jo hakemusvaiheessa. Aiemmat tutkimukset ovat osoittaneet iän, sukupuolen, koulutustausta ja sairauspoissaolojen lukumäärän olevan merkittäviä muuttujia tätä tutkittaessa. Tutkimuksen aineistona on yhden eläkelaitoksen vuosina 2016-2019 antamat ammatillisen kuntoutuksen ennakkopäätökset. Tutkimusmenetelminä käytetään khiin-neliötestiä, logistista regressiota sekä satunnaismetsää. Logistisen regression tuloksien mukaan tärkeimpiä ammatilliseen kuntoutukseen osallistumiseen vaikuttavia muuttujia ovat henkilön sukupuoli, kuntoutusrahan määrä, tietyt ammatit sekä vuosiansioiden määrä viimeisen viiden vuoden aikana ennen kuntoutusoikeuspäätöksen saamista. Ennustemalliksi luodun satunnaismetsän tulosten perusteella ammatilliseen kuntoutukseen osallistumista on mahdollista ennustaa. Positiivisen luokan ennustustarkkuus on selvästi parempi kuin negatiivisen luokan. Khiin-neliötestin, logistisen regression ja satunnaismetsän tuloksissa on kuitenkin myös toisistaan eroavia tuloksia.
  • Tossavainen, Tuuli (Helsingin yliopisto, 2021)
    Asymmetric information in insurance markets is the result of policyholders, the buyers of insurance, having more information about their own risk types and preferences than the insurer. Informational asymmetry between the insurer and policyholders can lead to non-optimal insurance prices and quantities which reduce market efficiency. While the presence of asymmetric information has been widely studied in several insurance markets, it has not been empirically studied in the Finnish automobile insurance market before. This thesis aims to fill this gap in literature. The Finnish automobile insurance market consists of two types of insurance. Motor liability insurance is required by law from all vehicles used for driving in traffic. Also, voluntary automobile insurance can be acquired in addition to the mandatory motor liability insurance. In this thesis, the presence of asymmetric information is studied by comparing the occurrence of motor liability insurance claims, conditioned with the pricing variables used by the insurer, between policyholders who only have a motor liability insurance policy and policyholders with an additional automobile insurance policy. The data set used in this thesis is from a single Finnish insurance company. The data set is from the year 2019 and it contains nearly 105,000 motor liability insurance policies. The data include all variables observed by the insurer. Several regression specifications and the widely used positive correlation test are used in this thesis to study the correlation between insurance coverage and motor liability insurance claims. The results of this thesis suggest that signs of asymmetric information are not present at aggregate level in the Finnish automobile insurance market in question. However, different subgroups of policyholders show signs of asymmetric information: After controlling for the pricing variables, policyholders with an automobile insurance policy with the largest coverage show a positive correlation between buying automobile insurance and motor liability insurance claims whereas policyholders with an automobile insurance policy with the third largest coverage show a negative coverage-claims correlation. However, the results from different regression specifications regarding different automobile insurance coverages were not unanimous and thus the results are left ambiguous. In addition, new policyholders considered as experienced drivers show a negative correlation between motor liability insurance claims and having automobile insurance coverage. On the contrary, policyholders considered as experienced drivers with 1–2 years of company experience do not show signs of asymmetric information. The result suggests that the insurer learns from its repeat customers as signs of informational asymmetry disappear over time. Moreover, policyholders considered as unexperienced drivers do not show signs of asymmetric information regardless of the length of their customership in the firm. The results are in line with previous research.
  • Tiililä, Nea (Helsingin yliopisto, 2019)
    The regulatory framework for financial regulation has developed much in the Europe after the financial crisis. The use of borrower based macroprudential instruments as regulatory tools has become popular among the European Economic Area -countries. Already 21 out of 31 EEA-countries have at least one borrower based macroprudential instrument in use. The most commonly used borrower based instruments are Loan to Value (LTV) limit, Loan to Income (LTI) limit, Debt to Income (DTI) limit, Loan Service to Income (LSTI) limit, Debt Service to Income (DSTI) limit, amortisation requirement and maturity limit. As these instruments are only recently introduced as regulatory tools in Europe, their effectiveness and transmission channels are still under discussion. The aim of this master's thesis is to contribute to the ongoing discussion of the effectiveness of the instruments. This thesis provides a broad literature review in order to understand the transmission of each of the borrower based instruments and to explore previous findings of the impacts of the instruments. Further, an empirical analysis is formed by using a panel vector autoregression (PVAR) model in order to study whether borrower based macroprudential instruments have any effect on housing market stability and real economy in the Europe. The data that is used to answer this question consists of growth rates of mortgage stock, house price index, construction index, household consumption and GDP. According to the literature review, the borrower based macroprudential instruments function through four different transmission channels. These are the credit demand channel, expectations channel, resilience channel and anti-default channel. The empirical analysis provides evidence that tightening the borrower based instruments reduces mortgage growth. House prices react negatively to a policy shock in the short run but positively in the long run. Construction reacts negatively to a policy shock. Household consumption on its behalf responds to a policy shock positively in the short run but negatively in the long run. Finally, GDP responds to a policy shock negatively. However, the result concerning construction growth is the only one which is statistically significant in a 95% confidence level and all the other results lack statistical significance. Overall, the empirical results of this thesis provide slight evidence that regulating borrower based macroprudential instruments restrain the growth of mortgage stock, which for its part should enhance the stability of housing markets in Europe. Further, the impact on economic growth is likely negative. However, the results are not statistically significant in a 95% significance level. The difficulties in fitting the model and the lack of significance may implicate that the chosen model might not be the most suitable one for studying the efficiency of borrower based macroprudential instruments.
  • Pedro, Gomes Santos (Helsingin yliopisto, 2022)
    The prevailing volatility of the price/spread related to catastrophe risk around this newly innovative type of instrument, called CAT bond, gave light to this literature. Contrarily to normal type of insurance coverage risks (such as cars, houses, etc...) risk associated to natural and human catastrophes is more unpredictable and costly for (re)insurance companies. Insurance and reinsurance companies found a way to finance this expensive risk by shifting it to investors through Insurance-Linked Securities (ILS), more precisely and successfully, CAT bonds. By cross-checking data and information from multitude of sources, I investigated which are the main determinants capable to influence the price, spread or coupon of a catastrophe bond on the primary market for those instruments. This paper gathers data of 284 catastrophe bonds issued in the market between January 2013 and October 2021 provided by Artemis deal directory. My research contains an introduction part on those innovative type of bonds, an overview on previous research regarding the question and their results, and some empirical data on the main goal of this work, which is defining what variables influence the price of the CAT bond in the primary market. OLS regressions techniques with heteroskedasticity and autocorrelation consistent standard errors are mainly used based on multifactor based models in order to identify the main determinants of the price. The work of Alexander Braun will be the main inspiration for this work, I will apply a couple of same techniques on my work, according to the data available and Stata limitations. The outcome of the larger model including the whole set of variables and crossed variables shows that the expected loss is the major influencers of the catastrophe risk prices for both the in-sample and out-of-sample estimation and across diversified subsamples and models. As per the conclusion from previous researchers, the expected loss variable has shown to impact positively the price of the coupon bond much more than any other variable.
  • Walta, Veikko (Helsingin yliopisto, 2020)
    The determinants of FDI have been a topic of interest in economics since the 1980s and this paper aims to contribute to this field. This study aims to measure how associated FDI is with the political risk as well as to see the extent of this relationship in Turkey in the years 1996–2017. The political risk is measured as a change in indexes that are provided by the World Bank, Freedom House, and Transparency International. These political indicators are Political Rights, Civil Liberties, the Corruption Perceptions Index, Regulatory Quality, Voice and Accountability, Rule of Law, Government Effectiveness, Control of Corruption, and Political Stability. The earlier literature on FDI and political risks is mostly empirical and there has not been much theoretical research. Chakrabarti analyzed the past studies on FDI and its determinants in 2001 and found out that in the earlier research, almost every explanatory variable of FDI except the market size was sensitive to small changes in the conditioning information set, casting doubt on the robustness of the results. There have also been conducted studies that address political risk or equivalent concepts. The 2005 research of Busse and Hefeker had the same topic as this paper but their data consisted of many countries and they employed two different panel models. One was a fixed-effects panel analysis while the other utilized a generalized method of moments estimator. I selected three model specifications for the time-series regression analysis. All three specifications have market size as a control variable and the other two also have the economy’s growth rate and trade openness. The third has the inflation rate as the final control variable. The data have a small number of observations which limits the options available for the empirical part of the study. Out of the nine political indicators, Regulatory Quality is the only political indicator that is not associated with FDI, while the results on the Corruption Perceptions Index and Control of Corruption are inconclusive. The rest six are associated with FDI. The Rule of Law index has the highest estimated coefficient value of the World Bank indicators and the Political Rights index has the highest estimated coefficient value of the Freedom House’s indicators.
  • Rissanen, Julius (Helsingin yliopisto, 2021)
    Abstract Faculty: Faculty of Social Sciences Program: Economics Study track: General Track Author: Julius Vili Henrik Rissanen Title: Comparing cost-effectiveness of short-term and long-term psychodynamic psychotherapies focusing on patients with depressive disorder and their work ability during a 5-year follow-up. Level: Master’s Thesis Month and Year: November 2021 Number of Pages: Keywords: Psychotherapy; cost-effectiveness; Work Ability; psychodynamic; randomized trial; Instructors: Roope Uusitalo, Lauri Sääksvuori, Costanza Biavaschi, Olavi Lindfors Deposited at: Helsingin Yliopiston kirjasto Other information: Abstract: Background: Mental health disorders pose significant burden to the society, for example, because of decreased work ability. Psychotherapy as one of the most important treatment methods also causes significant costs for the healthcare system. Putting effort into cost-effectiveness between the different therapy types can help promote better targeting of treatments and economic efficiency in society. Aims: Explore cost-effectiveness in improving work ability between short-term and long-term psychodynamic psychotherapy in patients with depression. Methods: The 192 depressive patients randomized to two psychotherapies of different lengths in the Helsinki Psychotherapy Study were measured in baseline and annually for five years. Work Ability Index (WAI) and Global Assessment of Functioning (GAF) as an effectiveness outcome measures were compared to the total direct costs with incremental cost-effectiveness ratios (ICER) between the treatments. Results: The total direct cost of short-term psychodynamic psychotherapy (SPP; €7,087) was significantly lower than for long-term psychodynamic psychotherapy (LPP; €19,959). The biggest explanatory factor between the cost of the treatments was protocol study therapy costs (SPP €1304; LPP €16,715). In addition, those randomized to the SPP had significant costs during the follow-up from the non-protocol auxiliary psychotherapy treatments (€5142) which were more than fives times compared to the LPP. All of these cost differences between the treatment groups were statistically significant. Psychotropic medication and outpatient care each averaged below €2000, and the differences weren’t statistically significant. Psychiatric hospitalization during the follow-up was rare but yielded significant costs to the associated patients. Differences of effectiveness between the treatment groups on the work ability were not statistically significant. The incremental cost-effectiveness ratio was highly unstable due to small differences in efficiency, but large differences in cost. Conclusions: The study found a clear difference in cost in favour of SPP without losing in the effectiveness of the treatment. However, patients in the SPP used a significant amount of non-protocol auxiliary psychotherapy treatments which may be an indication of insufficient therapy treatment. The absence of difference in the effectiveness can be thus attributed to the widespread utilization of additional treatments in the SPP. Going forward, expanding the study to account for the impact of patient’s suitability to the treatment, particularly in understanding SPP cost-effectiveness, would be worthwhile.
  • Ahonen, Elena Venla Maria (Helsingin yliopisto, 2017)
    The aim of this thesis is to demonstrate the importance of selecting feasible and, preferably data-based prior assumptions for the Bayesian time-varying coefficient vector autoregressive model (TVC VAR model for further reference) of Primiceri (2005) and Del Negro and Primiceri (2015). The TVC VAR model would be suitable for quantifying, for example, the impacts of different monetary policy or fiscal policy regimes. The biggest advantage of the TVC VAR model is that it takes into account both changes in economic policy and in the private sector behaviour. The latter feature makes the model very compelling to use, because the private sector plays an important role in facilitating mote stable change in monetary and fiscal policy regimes. In complex mathematical models, such as the TVC VAR model, the objectiveness of the model may be compromised by deliberate selection of parameters. The TVC VAR model uses the Bayesian approach, which means that the researcher’s choice for the prior assumptions for the model plays an important role in the estimation. Unfortunately, Primiceri’s (2005) approach for selecting hyperparameters for the model is poorly explained and difficult to follow. Given that the model depends only for a small number of hyperparameters, it might be possible that the model can be tuned in a predefined way. To investigate whether the TVC VAR model can be tuned according to a researcher’s preferences, I design a proof of concept approach for optimising the hyperparameters of the model according to a set of predefined results. In other words, my research question is: could one tune the TVC VAR model to produce results according to the researcher’s bias? In my proof of concept approach I tune the TVC VAR model for six different targets for the Finnish government consumption multiplier. Given that Finland is a small open economy, Primiceri’s (2005) original hyperparameter values for the United States are not feasible and other values have to be used. The results from my proof of concept analysis show that the TVC VAR model can be tuned for predefined results, which shows that the practical reliability of the model can be easily compromised. My findings highlight the need for a comprehensible, data-based approach for selecting the hyperparameters for the model.
  • Virtanen, Emil (Helsingin yliopisto, 2021)
    Tämän maisterintutkielman tavoitteena on tarkastella sitä, miten markkinakriisi vaikuttaa sijoittajien käyttäytymiseen ja dispositioefektin ilmenevyyteen ja sen muutoksiin. Aineisto on kerätty COVID-19-pandemian aikana ja koostuu suomalaisista sijoittajista. Tutkimuksessa pyritään lisäksi löytämään demografisia muuttujia, joilla dispositioefektin ilmenevyyttä voitaisiin selittää. Tutkimuksessa tuloksille luodaan viitekehys aiemmista empiirisistä tutkimuksista ja teorioista, joilla dispositioefektiä on havainnollistettu ja selitetty. Kirjallisuuskatsauksen jälkeen tutkimuksessa siirrytään empiiriseen osioon, jossa dispositioefektiä ja sen muutosta mitataan suomalaisista yksityissijoittajista koostuvan aineiston pohjalta. Aineisto koostuu kahdesta osasta, joista ensimmäinen pitää sisällään suomalaisten sijoittajien transaktioita ja toinen Helsingin pörssissä listattujen osakkeiden hintatietoja vuosilta 2017-2021. Dispositioefektin voimakkuuden laskemiseksi käytetään mallia, jossa verrataan sijoittajan realisoimattomien ja realisoitujen osakkeiden markkinahintojen suhdetta. Dispositioefektin muutosta COVID-19-kriisin aikana tutkitaan aikasarja-analyysilla, ja demografisten muuttujien yhteyttä dispositioefektin suuntaan ja voimakkuuteen puolestaan regressioanalyysilla. Tutkimuksen keskeiset tulokset osoittavat, että sijoittajat kärsivät dispositioefektistä. Tämä tutkimustulos tukee aiempia tutkimuksia. Aikasarja-analyysin tulokset indikoivat, että sijoittajien reaktio COVID-19-kriisiin vähentää dispositioefektin määrää ja että sijoittajat ovat halukkaampia realisoimaan myös tappioitaan COVID-19-kriisin alkamisen jälkeen. Tulokset tukevat aiempia tutkimuksia, joiden mukaan markkinan tilalla on vaikutusta sijoittajien dispositioefektin voimakkuuteen, ja teorioita, joiden mukaan sijoittajat ovat halukkaita realisoimaan tappioita, kun he olettavat markkinahintojen jatkavan laskuaan. Regressioanalyysin tulokset osoittavat naisten kärsivän miehiä voimakkaammasta dispositioefektistä, mikä on myös linjassa aiempien tutkimustulosten kanssa. Toisin kuin aiemmissa tutkimuksissa, tässä tutkimuksessa iällä ei havaittu olevan vaikutusta dispositioefektin ilmenevyyteen tai voimakkuuteen. Dispositioefekti on hyvin tunnettu ja empiirisesti koeteltu sijoittajilla havaittu käyttäytymisharha. Tämän tutkielman tulokset tukevat aiempaa tutkimusta ja antavat uutta tietoa siitä, kuinka sijoittajat reagoivat globaaliin markkinakriisiin ja siitä, miten dispositioefektin ilmenevyys ja voimakkuus muuttuvat sijoittajien kohdatessa markkinakriisin, jonka ominaispiirteitä ovat pelko ja epävarmuus.
  • Liukkonen, Sini (Helsingin yliopisto, 2020)
    High growth enterprises are important contributors to the aggregate economy but not much is known of their dynamics. Based on previous literature it is quite clear that their growth is usually not very persistent. The purpose of this study is to find the enterprise characteristics that positively affect the length of the growth period. In this study, extensive micro data from Statistics Finland is used. The data comprises of information from business register, financial statements, foreign trade, ownership and employee registers. Survival analysis methods are used to get information on the effects of different enterprise characteristic. The models account for the time-varying nature of the covariates and the coefficients. Based on the results, it is found that many of the characteristics have time-varying effects and the effects are not the same for all size classes of enterprises. It is quite clear though that access to foreign markets and innovativeness are important positive factors to the length of the growth period whereas size and age have negative effects. Survival analysis methods seem to fit quite well to this framework and they seem to produce robust results.
  • Kurki, Jaakko (Helsingin yliopisto, 2019)
    Wage discrimination occurs when employees of equal productivity receive different wages due to characteristics such as ethnicity, sex, or nationality, which do not affect their productivity directly. One of the common challenges in empirical research on wages has always been the challenge of determining individual employees` productivity. Professional sports leagues such as NBA (National Basketball Association) provide an ideal setting for the study of salary discrimination, as the salaries, players` backgrounds, and different statistical measures of players` performance throughout their whole careers are available publicly. Therefore, economists have used professional sports leagues when studying salary discrimination by ethnicity or nationality. The objective of this research is to find out whether salary discrimination by nationality occurs in the NBA during the period between 2016 and 2018. The research consists of a literature review that introduces previous findings on salary discrimination by nationality in the NBA, and an empirical part which aim is to find out whether this discrimination still occurs in the 2016 – 2018. The dataset of this thesis consists of statistics that measure NBA players' on-court performance and salary during the 2016 – 2017 and 2017 – 2018 seasons, as well as their nationality, and physical attributes. The empirical analysis is carried out using linear regression-analysis, which has been a standard in previous researches on salary discrimination by nationality in the NBA. Moreover, this study applies Blinder-Oaxaca decomposition, which is one of the standard tools used in salary discrimination studies in general. The statistical analysis of this study does not find discrimination by nationality against either foreign or domestic born NBA-players during our sample period. Nevertheless, foreign players earn, on average, around USD 500,000.00 higher annual salaries than their American contemporaries. However, according to our analysis, this difference is explained by foreign players' on-court performance rather than their nationality. Some previous researches find that foreign players from large economic markets receive sizeable salary premiums due to marketing possibilities in their home countries. However, this study does not find the market size of a player's home country to have a statistically significant effect on their salaries. The earliest literature on salary discrimination by nationality in the NBA dates back to the 1990s. Over the years, the results of previous researches have varied between foreign or domestic players being discriminated against by nationality. However, as different tools for statistical analysis on player performance have improved drastically and basketball has indeed become a global sport over the years, it seems that discrimination by nationality does not occur in the NBA anymore in 2019.
  • Kaur, Anmol (Helsingin yliopisto, 2020)
    This thesis aims to answer the question of whether monetary policy influences stock prices in the United Kingdom and Finland. These countries have been chosen due to their economic differences. The United Kingdom is an open relatively large economy with an independent monetary policy set by the Bank of England. Finland, on the other hand is a small open economy, and it is part of a monetary union called Eurozone. Hence, the monetary decisions are made by the European Central Bank for all the members of the union. The research is conducted for the time period of 15 years (2003-2018) with monthly time-series data. The method used in the thesis is the structural vector autoregression model which allows for solving the endogeneity issue through imposing restrictions on the structure of the model. Hence, short-run restrictions and long-run monetary neutrality are applied to the model. The model is analysed using the estimation as well as impulse response functions. In order to consider the macroeconomic environment, variables such as inflation, commodity prices, and industrial production are used in the model. Moreover, a dummy variable is used to account for the financial crisis of 2008. The results of the structural vector autoregression estimation show there to be a statistically significant negative effect of monetary policy on stock prices for both countries. The impulse responses show that as contractionary monetary policy is implemented, stock prices tend to decrease. Contrarily, expansionary monetary policy results in an increase of stock prices. The effect of a monetary policy shock is larger on the stock prices and dissipates quicker in the United Kingdom. For Finland, the effect is minor, and it takes longer to dissipate. However, the effect is statistically significant for both countries
  • Rönkkö, Niko-Petteri (Helsingin yliopisto, 2020)
    In this thesis, I analyze the causes and consequences of the Asian Crisis 1997 and simulate it with Dynare. The model includes financial accelerator mechanism, which in part explains the dynamics and the magnitude of the crisis via balance sheet effects. I find that the major components of the crisis were highly similar to other crisis that had happened in other emerging economies: High levels of foreign-currency denominated debt, unsound financial regulation, and fixed exchange rates with skewed valuation. Even though this simulation do not specifically incorporated different exchange rate regimes into the simulation, the previous literature draw a clear conclusion that flexible exchange rates lessen the shock’s effects on the economy. Thailand, as well as other ASEAN-countries during the crisis, faced severe economic contraction as well as changes in political landscape: Due to the crisis, Thailand’s GDP contracted over 10 percent, the country lost almost a million jobs, and the stock exchange index fell 75 percent. In addition, the country underwent riots, resignation of ministers, and several political changes towards more democratic institutions, even though faced some backlash and re-entry of authoritarian figures later. As the crisis worsened, IMF collected a large rescue package that was given to ASEAN-countries with preconditioned austerity policies. The simulation with recalibrated parameter-values seems to be relatively accurate. The dynamics and the impact of the crisis is captured realistically with correct magnitudes. The financial accelerator mechanism accounts a large part of the shock’s impact on investment and companies net worth, but do not account much on overall decline in output.
  • Snellman, Oliver (Helsingin yliopisto, 2019)
    It has lately become a common practice among national authorities with macroeconomic mandates to build large Dynamic Stochastic General Equilibrium (DSGE) models to assist in forecasting and policy analysis. The Finnish Ministry of Finance has also developed a small open economy New Keynesian DSGE model, “KOOMA”. As DSGE models try to emulate the key features and dynamics of the economy, the crucial question is, how well do they function in accordance with reality? An answer to this question can be searched by using Structural Vector Autoregression (SVAR) models, which are natural econometric counterparts to DSGE models and are better suited for analyzing data. The aim of this study is to evaluate the calibration of KOOMA with a SVAR model, which is identified with sign restrictions. I compare impulse response functions from the SVAR model, which are found both statistically significant and robust to changes in model specifications, to the equivalent impulse response functions from KOOMA. The findings suggest, that KOOMA generally produce impulse responses with same signs as the SVAR model, but there are some differences in the magnitudes and persistence of the responses.
  • Li, Tingyang (Helsingin yliopisto, 2020)
    This thesis examines the macroeconomic impact of Covid-19, constructing a DSGE model incorporating wage rigidity and consumption habit. This paper captures the characteristics of the Finnish economy, such as high wages and high consumption habits, and aims to analyze the macroeconomic impact of Covid-19 in Finland. Based on the New Keynesian DSGE model and combined with the SVAR method, focusing on the adverse effects of Covid-19 and analyzing how to mitigate its negative effects. After building the DSGE model, Bayesian estimation was performed using the parameters of Kilponen (2016) as the prior distribution, after which impulse response analysis was performed. At the same time, the effectiveness of fiscal policy and monetary policy is analyzed. The results of the empirical model support the conclusions in the theoretical model. The results show that the decline in utility due to insufficient consumption preferences significantly impacts consumption and output, causing aggregate consumption to decline and remain below steady-state levels for a long time. The level of labor supply is negatively affected by underconsumption. But the shock to consumer preference increased investment, offsetting some of the negative shock to output. Inflation and real interest rates also took a downward hit. Real interest rates first fall and then rise but remain below a stable level for a long time as the supply of capital rises when the demand for capital falls. A negative shock to technology causes aggregate consumption and aggregate output, and labor and capital goods to fall. In contrast, a fall in capital value causes Tobin's q to fall. Looking at the impact time of the impulse response, we find that the negative impact on macroeconomic variables is large and long-lasting. A positive government spending shock of one standard deviation would directly increase aggregate output, but its impact on output would be diminished. Compared with fiscal policy and monetary policy, the role of government spending is more likely to bring the economy into a stable state, and its response is more sensitive. We find that fiscal policy has a more significant impact on macroeconomic regulation; this suggests that monetary and fiscal policy need to work together in the context of high inflation and low interest rates. Fiscal policy drives economic recovery and can provide strong support for the realization of monetary policy.
  • Peltola, Eemeli (Helsingin yliopisto, 2021)
    Tässä tutkielmassa käsittelen finanssisyklien säännönmukaisuuksia ja selvitän niiden paikkansapitävyyttä Suomessa. Finanssisyklit ovat makrotaloustieteen tutkimuskohde, joka on läheistä sukua reaalitalouden muuttujiin keskittyvälle suhdannesyklien tutkimukselle. Finanssisyklit muotoutuivat tutkimusaiheeksi vuosien 2007–2009 finanssikriisin jälkeen, kun rahoitusmarkkinoiden ylikuumentumisia ja romahduksia ruvettiin tutkimuksissa tarkastelemaan syklisenä liikkeenä. Finanssisyklien säännönmukaisuuksia, eli niin kutsuttuja tyyliteltyjä faktoja, voidaan käyttää makrotaloustieteen mallien muotoilemiseen. Kirjallisuudessa finanssisyklit identifioidaan yleisimmin luottokantojen, asuntojen hintojen ja asuinkiinteistöjen hintojen avulla. Näistä tunnistettujen syklien ominaisuuksia verrataan usein BKT:n sykleihin. Tutkielmassani tarkastelen Suomen luottokannan, asuntojen hintojen ja BKT:n syklejä ajanjakson 1970Q4–2020Q3 kattavalla neljännesvuosiaineistolla. Lisäksi tutkin Suomen lainakannan, asuntojen hintojen ja BKT:n syklejä ajanjakson 1905–2017 kattavalla vuosiaineistolla. Käytän analyysissäni käännekohtamenetelmää, havaitsemattomien komponenttien malleja ja CF-suodatinta. Käyttämäni menetelmät ja aineistot antavat yhdenmukaisen kuvan siitä, että Suomen luotto- ja lainakannoissa, asuntojen hinnoissa sekä BKT:ssa on 8–20 vuoden mittaisia keskipitkän aikavälin syklejä, jotka liikkuvat ajallisesti tarkasteltuna läheisesti yhdessä. Tuloksieni mukaan luotto- ja lainakantojen sekä asuntojen hintojen syklien värähdyslaajuus on BKT:n syklejä suurempaa. Tuloksistani on myös havaittavissa, että luotto- ja lainakantojen sekä asuntojen hintojen syklien huipuilla on taipumusta ajoittua finanssikriiseihin sekä muihin epävakaisiin ajanjaksoihin rahoitusmarkkinoilla. Tulokseni vastaavat kirjallisuudessa vallitsevia käsityksiä finanssisyklien tyylitellyistä faktoista kehittyneissä maissa. Tutkimukset eivät ole yksimielisiä siitä, onko finanssisyklien pituus ja värähdyslaajuus kasvanut vuoden 1985 jälkeen. Tutkielmassani arvioin tutkimushypoteesia CF-suodattimen ja havaitsemattomien komponenttien mallien avulla. Saamani tulokset viittaavat siihen, että Suomen lainakannan ja asuntojen hintojen syklit ovat olleet vuoden 1985 jälkeen pidempiä kuin vuosina 1950–1984, mutta ainoastaan lainakannan syklien värähdyslaajuus on kasvanut. Uudemmissa tutkimuksissa on tutkittu vähemmän sitä, kestävätkö finanssisyklien noususuhdanteet keskimäärin pidempään kuin laskusuhdanteet, ja onko tämä epäsymmetrisyys suurempaa kuin BKT:n sykleillä. Käsittelemäni tutkimuksen sekä käännekohtamenetelmällä saamieni tuloksien mukaan finanssisyklien noususuhdanteet kestävät laskusuhdanteita pidempään, mutta tämä epäsymmetrisyys ei ole suurempaa kuin BKT:n sykleillä.
  • Mostýnová, Michaela (Helsingin yliopisto, 2019)
    In Finland, entrepreneurs (both employers and self-employed) are, compared to salaried employees, free to increase their compulsory retirement insurance contributions to the public pension fund; this being an alternative to additional saving for retirement in private pension funds. This thesis seeks to identify and further examine factors which supposedly influence entrepreneurs‘ perceived sufficiency of their retirement insurance payments . The purpose is to subsequently recommend retirement policy designs which would incentivize Finnish entrepreneurs to increase their contributions to the public pension fund. The empirical section of this work was conducted on a sample of 2 294 entrepreneurs (1 533 self-employed and 761 employers) who took part in the 2017 Labor Force Ad hoc Survey on Entrepreneurship carried out by Statistics Finland. The initial hypotheses gave rise to four categories of variables, presumably affecting sufficiency of retirement insurance contributions perceived by the study sample; namely, ’Personal characteristics & Business background’, ’Motivation’, ’Future perspectives’ and ’Job satisfaction & excitement’. The obtained results suggest that the majority of the selected variables have an effect on entrepreneurs’ perceived sufficiency of their pension insurance contributions. Besides, the factors identified as negatively affecting the perceived sufficiency of retirement insurance payments were more frequently present in the group of self-employed compared to the group of entrepreneurs (employers). Therefore, it is expected that the self-employed are more prone to pay themselves insufficient pension insurance contributions. However, all these factors are considered as incorrigible since they stem from the very nature of complex human behaviour. In this sense, the behavioural approach seems to be highly relevant when forming retirement insurance policies seeking to encourage prudent saving behaviour. This study applies an alternative approach of behavioural economics to the problematics of retirement saving. The first part of the thesis outlines foundations of behavioural economics which serve as a theoretical background for further analyses. For instance, propositions of procrastination, self-control and mental accounting are discussed.
  • Sandell, Hanna (Helsingin yliopisto, 2020)
    The inaccuracy of transport infrastructure projects’ cost estimation has become large issue especially because the amount of large mega projects has been increasing during past few years. The cost estimation inaccuracy is problematic because it biases the results of cost-benefit analysis, which is used to measure the profitability of a project. Subsequently this bias can lead to the misallocation of scarce resources. Besides the construction costs, cost estimation includes the computation of owner’s indirect costs. In this thesis, owner’s indirect costs cover the construction management costs and design costs of the project. According to the current instructions, indirect costs are calculated using fixed default values. As the currently used calculation method does not take the project’s individual properties into account, need for alternative approach has increased. Thus the objective of this thesis is to forecast owner’s indirect costs in the late phases of the infrastructure projects by applying two different machine learning models: linear multiple regression model and artificial neural network model. Additionally, the aim is to study, whether machine learning models provided can outperform the currently used instructions in the prediction of indirect costs. Aim of well-functioning forecast model would be to improve the cost estimation’s accuracy level. In this thesis, owner is defined as the government and indirect costs are only forecasted in later phases of the project. Research question is attempted to solve by applying two commonly used machine learning models: artificial neural network and multiple regression model. Neural network used in this thesis is a feedforward network, which learning mechanism is based on backpropagation algorithm. Multiple regression model utilizes traditional OLS method in the estimation of parameters’ values. Models are constructed with data provided by Finnish Transport Infrastructure Agency. Data includes infrastructure projects’ initial data and the actual shares of design and construction management costs of each project. As an outcome, this thesis provides two preliminary forecast models for owner’s indirect costs. The results also indicate that the neural network and regression model are able to forecast owner’s indirect costs in both categories with higher accuracy compared to the current instructions. Furthermore, study aided to recognize influential variables affecting the indirect costs. During the research process, also few improvements for further development of the forecast models were identified. From the machine learning models, neural network performs better in forecasting the design costs and regression model is able to forecast the construction management costs with slightly better accuracy. These results support the conclusion that costs with uncertain and missing information can be forecasted more precisely with more complex machine learning models, such as the artificial neural network. On the other hand, costs with comprehensive knowledge can be accurately predicted with simpler models, such as the multiple regression.