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.

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.

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.

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.

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.

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.

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.

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.

Despite continuous improvements in treatments, childhood cancers are among the most common causes of death for children in Finland. The cancer treatments are often arduous and have long-lasting effects even beyond the person diagnosed. Estimating these effects is important, since they can affect the cost-effectiveness of many policies. This thesis focuses on estimating the effects of childhood cancer on parental labour market outcomes, especially on the earnings gap between genders. Estimating the causal connection between health and socioeconomic variables is difficult for many reasons. In this thesis, a quasi-experimental method called "staggered differences-in-differences" is employed to solve this problem. In this method, families where cancer is diagnosed are compared to those that are diagnosed at a different time, and this way the true causal effect can be estimated. The thesis used administrative data from all childhood cancer diagnoses in Finland during years 1999-2017. The results show that childhood cancer reduces parents' income significantly. In short run, the effect is around 30% of the income before the diagnosis for mothers and around 7% for fathers. For mothers, the decline in employment is also significant. The welfare state provides support to these families to the extent that the decline in the income after transfers is not as large. The gender earnings difference increases around 20% in the short run, and increases also in families where mother is the main provider in the years before the diagnosis. My results are robust to different checks, including alternative estimators to correct for possible cohort-heterogeneous effects. The previous research is scarce and has provided differing estimates, but the results of this thesis are in line with the most relevant literature. The decline in earnings can be caused by the need to take care of the child, mental health effects or declined accumulation of human capital. While it is hard to suggest policy changes based on these results alone, the current benefits around ill children are short in duration and focused on one person and the results indicate that perhaps a longer benefit scheme distributed more evenly between genders might provide different outcomes.

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.