Browsing by master's degree program "Master's Programme in Economics"
Now showing items 1-20 of 175
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(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.
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(2023)This thesis focuses on the investigation of adverse selection and moral hazard in the Finnish entrepreneurial insurance system. The thesis builds upon previous research on moral hazard and adverse selection in insurance markets, but focuses specifically on the social insurance market for entrepreneurs within sickness and parental allowances. This topic is of interest as mandating social insurance for entrepreneurs is vital, but often lacking due to the flexible nature of entrepreneurial activity. As a result, the social insurance systems may be subject to adverse selection and moral hazard. Rich panel data on insurance contributions of entrepreneurs in Finland allows me to measure the extent of asymmetric information both overall and dynamically. To test the former, I use a positive correlation test. In particular, the test looks at the probability of sickness or having a child in relation to insurance contributions. The results indicate a slight positive correlation between sickness risk and insurance contributions as well as the probability of having a child and insurance contributions. A more significant result is found for the risk of having children in a dynamic sense, showing a strong indication of a rise in insurance contributions around the time of receiving parental allowance. However, the results are more ambiguous in the case of sick pay. These results are robust to several controls as well as two separate identification strategies. Due to the endogeneity of illness or choosing to have children, causal conclusions cannot be drawn from the results.
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(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.
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(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.
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(2024)T\"am\"a maisterintutkielma tutkii Suomen sis\"all\"a esiintyvi\"a alueellisia eroja ty\"omarkkinoiden kohtaannossa vuosina 2011-2022. Kohtaannolla tarkoitetaan t\"ass\"a tutkielmassa ty\"ott\"omien ty\"onhakijoiden ja avointen ty\"opaikkojen/vakanssien kohtaamista ty\"omarkkinoilla. Kohtaanto heikkenee silloin, kun avointen ty\"opaikkojen ja ty\"ott\"omien ty\"onhakijoiden m\"a\"ar\"at kasvavat samanaikaisesti. T\"all\"oin sanotaan usein, ett\"a ty\"omarkkinoilla siirryt\"a\"an ylemm\"alle Beveridge-k\"ayr\"alle. Vertailen alueellisia eroja pitk\"alti ty\"omarkkinoiden etsint\"a- ja kohtaantoteorian valossa. Teorian mukaan ty\"omarkkinoilla uusia ty\"opaikkoja ei synny kitkatta, vaan ty\"omarkkinoiden osapuoliin (ty\"onantajat ja -hakijat) kohdistuu kustannuksia heid\"an osallistuessaan rekrytointiin/ty\"onhakuun. Lis\"aksi niin ty\"onantajilla kuin -hakijoillakin on tietyt rajahy\"odyt, joita alemmalla hy\"odyll\"a he eiv\"at suostu sopimukseen. T\"alloin ty\"omarkkinoilla kohtaavat vain sellaiset parit, jotka t\"aytt\"av\"at toistensa vaatimukset. T\"at\"a prosessia mallintaa kohtaantofunktio \(M=M(U,V)\), jossa M on syntyneiden ty\"osopimusten m\"a\"ar\"a, U on ty\"ott\"omien m\"a\"ar\"a ja V on vakanssien m\"a\"ar\"a. Tarkastelen vuosien 2011-2022 kehityst\"a ja alueellisia eroja k\"aytt\"aen sek\"a kohtaantofunktiota ett\"a Beveridge-k\"ayr\"a\"a eli vakanssien ja ty\"ott\"omyyden suhdetta. Kohtaantofunktion estimointi osoittaa sen tehokkuuden laskeneen maanlaajuisesti, joskin v\"akiluvultaan suuremmissa maakunnissa havaitaan parempaa menestyst\"a pienempiin verrattuna. My\"os Beveridge-k\"ayrien empiirinen analyysi osoittaa kohtaanto-ongelman olevan yhteinen, vaikkakin eri maakunnissa eri suuruinen. Lis\"aksi tutkin, kuinka julkiseen ty\"onv\"alitykseen ilmoitetut avoimet ty\"opaikat ovat muuttuneet vuosina 2011-2022, ja kuinka niiden ominaisuudet ovat vaikuttaneet t\"all\"a ajalla niiden t\"ayttymiseen alueittain ja kansallisesti. Havaitsen suurten yritysten osuuden julkisessa ty\"onv\"alityksess\"a kasvaneen merkitt\"av\"asti ja osa-aikaisen ty\"on osuuden nousseen kokop\"aiv\"aisten ty\"opaikkojen kustannuksella. T\"all\"akin aineistolla lasketut aluekohtaiset kiinte\"at vaikutukset viittaavat kohtaannon heikentymisen olevan yhteinen ilmi\"o, jonka suhteen v\"akiluvultaan suuremmat alueet kuitenkin p\"arj\"a\"av\"at keskim\"a\"arin hieman pienempi\"a verrokkejaan paremmin.
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(2022)Tiivistelmä Tiedekunta: Valtiotieteellinen tiedekunta Koulutusohjelma: Taloustieteen maisteriohjelma Opintosuunta: Taloustieteen yleinen opintosuunta Tekijä: Kimmo Nevanlinna Työn nimi: Älysopimusalustojen hinnoittelun tehokkuus Työn laji: Maisterintutkielma Kuukausi ja vuosi: 11/2022 Sivumäärä: 48 Avainsanat: Lohkoketju, satunnaiskävely, kryptovaluutta, älysopimus Ohjaaja tai ohjaajat: Jani Luoto Säilytyspaikka: Helsingin yliopiston kirjasto Muita tietoja: Tiivistelmä: Maisterintutkielma tutkii kolmen älysopimuksiin erikoistuneen kryptovaluutan Ethereumin, Cosmoksen ja Tezosksen hinnan satunnaiskävelyn hypoteesia. Kryptovaluutat ja lohkoketjut ovat nousseet julkiseen keskusteluun viime vuosina, kun niiden hinnat ovat vaihdelleet villisti ja niiden hintojen muutoksia seurataan nykyään suurissa kansainvälisissä ja kotimaisissa talousuutisissa, mutta ymmärrys hintojen muutosten takana on vajavaista. Kryptovaluutoista tunnetuin Bitcoin sai alkunsa vuonna 2009, mutta viimeisen viiden vuoden aikana älysopimukset ovat nousseet myös julkiseen keskusteluun. Kryptovaluuttoja pidetään kuitenkin yleisessä keskustelussa keskenään samanlaisina eikä niiden eroja ymmärretä tarpeeksi hyvin. Kiinnostukseni älysopimuksiin ja niiden mahdollisuuksiin syttyi vuonna 2018 ja se kiinnostus sai minut tutkimaan asiaa taloustieteen näkökulmasta maisterintutkielman verran. Tämä maisterintutkielma selittää mitä älysopimukset ovat ja miten niiden käyttö lisää sen kryptovaluutan kysyntää, jonka päällä älysopimus suoritetaan. Tutkielmassa käydään myös läpi mitä lohkoketjut ovat. Empiirisessä osuudessa käytetään metodina autokorrelaation tutkimista tuottoaikasarjasta. Tehokkaassa hinnan muodostuksessa ei pitäisi löytyä autokorrelaatiota. Autokorrelaatio mitataan Ljung-Boxin menetelmällä päivittäisistä tuotoista 1.1.2019-31.6.2021. Toisena menetelmänä käytetään yksikköjuuren estimointia. Tämä tutkitaan Dick-Fullerin testillä. Yksikköjuuri löydetään kahdesta suuremmasta kryptovaluutasta Ethereumista ja Cosmoksesta, mutta ei pienemmästä Tezosksesta. Lopputuloksena todetaan, että isommat kryptovaluutat vaikuttavat olevan jotakuinkin tehokkaat satunnaiskävelyn osalta, mutta kaikki kolme kryptovaluuttojen tuottoaikasarjaa sisältävät autokorrelaatiota.
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(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.
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(2024)Banking crises have been found to cause significant fiscal and real costs for the economy. For this reason, macroprudential policymakers have developed various analytical models for predicting new banking crises ahead of time. With this information policymakers can undertake targeted countermeasures to reduce the negative impacts. In the prediction exercise binary regression models (especially logit) have been the main analytical tool for long. However, due to the complex dynamics and rare occurrences, accurate crisis prediction remains a difficult task for these models. In line with the recent developments in technology and artificial intelligence, scholars have started investigating the possibilities of using machine learning methods in banking crisis prediction. Despite the promise of more flexible distributional assumptions and enhanced modeling of non-linear relationships, the early results on predictive performance have been mixed. One explanation for this could be the large variety of models and empirical setups that different authors have used. As a result, it remains unclear whether the results are driven by changes in the underlying empirical setups, or the superiority of the machine learning models themselves. To investigate this problem, this thesis collects out-of-sample prediction results from eleven banking crisis papers published between 2017 and 2023. After implementing a normalization procedure to enhance comparability between the papers, the results are pooled for analysis to gain insights into which machine learning models perform the best. Additional robustness checks are also carried out to investigate the stability of the results. This thesis makes two main contributions to the literature. The first one is finding systematic differences in predictive performance between machine learning models. Neural network, random forest and boosted/bagged tree models have on average delivered the best predictive performance in comparison to logit models. In contrast, k-nearest-neighbors, decision tree and support vector machine models consistently underperform the logit benchmarks. The second contribution is creating novel connections between the banking crisis and machine learning literatures. The empirical results obtained in this thesis are contrasted and found to be aligned with the machine learning literature. In addition, a critical review of the practical implications resulting from the use of machine learning is conducted. Issues with interpretability, modeling and class-imbalances are highlighted.
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(2024)Aiemmin on todistettu, että rekrytoinneissa esiintyy syrjintää. Syrjinnän kohteita ovat yleisesti olleet naiset, ulkomaalaistaustaiset tai muut vähemmistöt. Rekrytointisyrjinnän vähentämiseksi yksi kehitetty menetelmä on anonyymi rekrytointi. Anonyymissa rekrytoinnissa rekrytoijalta piilotetaan hakijoita yksilöiviä tietoja, kuten nimi, ikä ja sukupuoli. Anonyymia rekrytointia käytetään myös Metsähallituksessa. Tutkielma käsittelee Metsähallituksen toteutusta anonyymista rekrytoinnista vastaamalla kahteen tutkimuskysymykseen: Miten anonyymi rekrytointi on vaikuttanut eri ryhmien palkkaamistodennäköisyyksiin ja organisaation monimuotoisuuteen? Millaisia kokemuksia ja oletuksia rekrytoinneilla esihenkilöillä on anonyymista rekrytoinnista? Tutkielman aineisto koostuu rekrytointien tiedoista sekä rekrytoinneille esihenkilöille lähetetyn kyselyn vastauksista. Tutkielman analyysiin käytetty rekrytointiaineisto sisälsi 251 palkatun hakijan tietoja, kuten iän ja sukupuolen. Palkatuista 17 oli palkattu anonyymia rekrytointia hyödyntäen. Tutkielman aineiston toinen osa koostui kyselyn vastauksista. Kysely lähetettiin 88 esihenkilölle, joista 26 vastasi kyselyyn. Vastanneista henkilöistä yhdeksän oli käyttänyt vähintään kerran anonyymia rekrytointia Metsähallituksessa. Lähetetty kysely oli lyhyt, sisältäen 10 kysymystä. Kysymykset oli aseteltu hieman eri tavoin sen mukaan, oliko vastaaja käyttänyt anonyymia rekrytointia vai ei. Rekrytointiaineiston osalta tutkielmassa käytetään tuloksien saamiseksi lineaarista regressiomallia usealla muuttujalla. Käytetty malli tutki eri muuttujien, kuten anonyymin lomakkeen, hakijan iän ja sukupuolen vaikutuksia hakijan palkkaamistodennäköisyyteen. Palkkaamistodennäköisyys jokaisen tehtävän osalta tutkielmassa laskettiin jakamalla tehtävään palkattujen lukumäärä hakijoiden kokonaismäärällä, olettaen jokaisen hakijan olleen pätevä hakemaansa tehtävään. Kyselyn vastauksia tutkielmassa käsiteltiin aineistolähtöisesti laadullista päättelyä hyödyntäen. Esimerkiksi avoimia vastauksia teemoiteltiin tutkielmassa eri teemoihin ja tätä kautta esiteltiin teemakohtaisesti esiin nousseita asioita vastauksista. Monivalintakysymysten osalta vastauksien jakaumia tarkasteltiin kysymyskohtaisesti sekä vertailemalla vastauksia anonyymia rekrytointia käyttäneiden ja ei-käyttäneiden esihenkilöiden välillä. Rekrytointiaineistoa ja regressiomallia hyödyntämällä tutkielmassa havaitaan anonyymin rekrytoinnin parantaneen naisten palkkaamistodennäköisyyttä jopa 30 %-yksikköä. Kun taas havaittu vaikutus yli 50-vuotiaiden palkkaamistodennäköisyyteen on negatiivinen ja suuruudeltaan noin -9,5 %-yksikköä. Muiden tutkittujen muuttujien osalta tutkielmassa ei löydetty merkittäviä tuloksia anonyymin rekrytoinnin vaikutuksesta palkkaamistodennäköisyyksiin. Kyselyn vastauksista tutkielmassa huomataan, ettei vastaajat kokeneet anonyymin rekrytoinnin vaikuttaneen rekrytointiprosessiin tai hakijoiden yhdenvertaiseen kohteluun. Kyselyyn perustuen Metsähallituksen henkilöstö on avoin kokeilemaan anonyymia rekrytointia. Henkilöstö korosti menetelmään siirtymisessä organisaatiosta tulevan kannustamisen sekä menetelmään kouluttamisen tärkeyttä. Kyselyn vastauksien avulla tutkielma havaitsee myös pieniä ongelmia anonyymin rekrytoinnin toteutuksessa. Selkein havaittu ongelma oli se, että hakijoiden taustatiedot paljastuivat anonyymissa rekrytoinnissa helposti rekrytoijalle erinäisistä syistä. Tutkielma osoitti, että anonyymilla rekrytoinnilla on merkittäviä vaikutuksia tiettyjen ryhmien palkkaamistodennäköisyyksiin Metsähallituksessa sekä organisaation henkilöstön olevan avoimia kokeilemaan anonyymia rekrytointia. Tutkielmassa havaitaan Metsähallituksen anonyymin rekrytoinnin toteutuksessa ongelmia, ja menetelmän teorian mukaisen käytön takaamiseksi olisi tärkeää pohtia mitä tietoja hakijoista piilotetaan rekrytoinnin alussa. Piilotettavia tietoja miettiessä on tärkeää huomioida implisiittiset tiedot, joita rekrytoija voi saada esimerkiksi hakijan valmistumisvuosista.
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(2024)The possibility for patients to renew electronic prescriptions online was introduced in Finland in November 2015. This thesis sets out to answer whether the adoption of this new feature contributed to the medication persistence of antidepressant users by reducing the effort involved in renewing prescriptions. Online renewal can be considered a part of a larger programme to utilise technology to improve Finnish health care, whereas a major necessary intermediary step towards the adoption was the implementation of electronic prescribing. Previous research by Böckerman et al. (2023) documenting an increase in benzodiazepine use following eprescribing serves as an example of the access-improving potential of technology. In addition to describing the institutional setting, this thesis includes a literature review of the economics of medication adherence and health information technology. The methodology section provides an overview of the chosen methods, a mixed effects Cox model with a random intercept, i.e. a frailty model, and a linear probability model with a difference-in-differences estimator and patient fixed effects. While the results of the frailty models without time controls estimated that the hazard of renewal was around three times larger for prescriptions renewable online, this result was contradicted by the last frailty model with time dummies, which suggested that the hazard of renewal for prescriptions renewable online was half of that of prescriptions not renewable online. Both the preliminary inspection of cumulative incidence curves as well as the supplementary analysis with the linear probability model corroborate the notion that online renewal is associated with lower renewal rates. A causal interpretation would be that online renewal had a modest negative effect on the probability of renewal, likely explained by misallocation of online renewal requests to doctors unfamiliar with the patients, resulting in the rejection of those requests. However, given the presence of major underlying trends towards longer-running prescriptions, culminating in the legislative extension of prescription validity at the start of 2017 right after the end of the study period of this thesis, further analysis is needed to verify these findings.
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(2024)This thesis studies the extent to which a state of the art Bayesian model, Bayesian predictive synthesis, can improve the nowcasting of Finnish GDP. GDP is the most looked after and thus the most nowcasted economic variable. The true values for GDP are published with a significant delay and revised later on, which highlights the necessity of well-performing forecasting models. In this thesis I replicate an existing study on Bayesian predictive synthesis in Finnish setting and then extend the framework to study forecast accuracy for GDP change. In the first part of the thesis, the theoretical background of the BPS model framework is studied in detail after which the application follows. In the empirical study six projection models are formed as dynamic linear models which are then synthesized with the novel Bayesian predictive synthesis. These results are benchmarked against the existing Bayesian VAR model that is used by Bank of Finland. In the empirical application I find that the Bayesian predictive synthesis is unable to improve the projection models' forecast accuracy. I also find that the synthesis for GDP levels performs better than the synthesis for GDP change. In the literature the synthesis model is mainly used to project nonstationary series. Results from this study support the assumption that BPS framework applies better for nonstationary projections. Also, the model is found to be very sensitive to the set of projections and parameter selection, which highlights the need for expert opinion in choosing the right models to synthesize for each application. Based on this research, this stand-alone BPS framework is not suitable to replace existing models for GDP nowcasting. For future research, it is recommended that BPS model is used to synthesize the already existing nowcasting models for improving these models.
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(2022)Regret is the value lost by playing an action on the current round of a iterative game. The idea of regret matching is to generate strategies that minimize regret, since it is guaranteed by folk theorem to converge to Nash Equilibrium in a two-player zero-sum game. Storing cumulative regrets after each iteration enables to use of regret matching. It is an algorithm that chooses next iteration strategy based on the cumulative regrets of the actions. This procedure itself would converge to Nash Equilibrium in a normal form game zero-sum game. For extensive form game the data storing will become too resource demanding, when the game size is even moderate. However, it's possible to minimize regret on each information set separately using counterfactual regret. Counterfactual regret is calculated by using counterfactual values. Counterfactual value calculates expected value given that player tries to get to an information set and play a certain action in it. The difference between the action and expected value of the information set is counterfactual regret. Similarly minimizing regrets converges toward Nash Equilibrium. Using counterfactual regret minimization framework I create an iterative self-play algorithm to solve two-player zero-sum imperfect information games. In this thesis I work with last betting round of limit Hold'Em. CFR+ uses improved strategy averaging, does not store negative regrets and alternates between strategy updating player. I did eventually manage to construct CFR+ algorithm, and it seems extremely effective compared to earlier versions of the algorithm.
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(2023)Taxation is a critical tool for development, as well-designed tax systems can generate greater revenues to fund public goods and investments that drive productivity. However, lower-income countries often raise only a small percentage of their gross domestic product (GDP) in taxes compared to higher-income countries. The gap in revenue is particularly striking for property taxes. This thesis begins with a literature review on taxation in developing countries and property taxation in general, emphasizing the challenges of property taxation in developing countries. It then provides relevant background information on Kenya, discussing inequality, general taxation, and property taxation. Using survey data from the Kenya Integrated Household Budget Survey 2015-2016, the thesis then investigates the distribution of property value and income among Kenyan households. It then explores the potential revenue and distributional effects of two property taxation models while also considering potential revenue loss from taxing households with insufficient income or savings. The trends between household income and property value indicate that higher annual incomes correlate with higher property values and vice versa. However, low-income individuals also owned higher-value properties, leading to liquidity problems. A 2% linear property tax rate model revealed a heavy tax burden on lower-income households and an overall revenue potential of 2.38% of total survey income or 0.94% of 2016 GDP. The study observed significant decreases in revenue potential when adjusting revenue to account for the ability to pay. This research also modeled a property tax rate payable only upon reaching a specific income threshold to address liquidity problems. In this model, the tax burden shifted to higher-income households with an overall potential tax revenue of 1.91% of total survey income or 0.76% of GDP. In conclusion, the observed trends, such as the high prevalence of inability to pay, relatively low revenue potential, and the administrative effort required for property taxation, suggest that reforming property taxation may not be the most practical approach for increasing revenue in Kenya.
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(2024)Asuntojen hintojen tekijät ovat niin asuntosijoittajan kuin omistusasujankin kannalta mielenkiintoisia. Tässä työssä esittelen empiirisen mallin jolla pyrin selvittämään paljonko eri tekijät vaikuttavat vanhojen omistusasuntojen neliöhintoihin. Erityisen huomion kohteena on lyhyet sekä pitkät markkinakorot. Työssä käytetty regressiomalli on yleistetty pienimmän neliösumman paneeliregressiomalli (GLS) kaupunki- ja aikakohtaisilla kiinteillä vaikutuksilla, heteroskedastisuuskorjauksella sekä autoregressiivisellä, liikkuvan keskiarvon ARMA(1,1)-komponentilla. Mallilla tuloksista saadaan lähes heteroskedastisuus- ja autokorrelaatiorobusteja. Lisäksi rakennetaan asuntosijoituksen ja 10:n vuoden valtionlainan tuottojen erotusta mallintava Ylituotto-muuttuja. Malli ennustaa 1%-yksikön kasvun lyhyissä koroissa olevan yhteydessä - 458,3€ ja pitkissä koroissa -41,5€:n muutokseen neliöhinnoissa. Väkiluvun havaitaan kummassakin mallissa kasvattavan asuntojen hintoja kaupungissa yhden sentin jokaista uutta asukasta kohden. 1%:n ylituotolla taas havaitaan hieman alle 100€:n käänteinen yhteys asuntojen neliöhintoihin. Tulokset ovat teorian ja kirjallisuuden perusteella odotettuja mutta mallien tulokset eroavat toisistaan paljon. Tarkastelujakson pidentäminen parantaisi tuloksia.
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(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.
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(2023)Personalized pricing as a pricing strategy has become possible as a result of technological advancement. Personalized pricing uses data to determine prices that differ from uniform pricing and as a result, welfare effects change. This master thesis uses a two period oligopoly model to analyze welfare effects of personalized pricing and then applies modifications to the model to account for EU Regulations. The model finds that regulation helps mitigate negative welfare effects by reducing the amount of inefficient switching and a price ceiling helps to reduce the appropriation effect for a consumer with a high willingness to pay. A case study is used to illustrate a use case for an oligopolistic market to bring real-world context to the theoretical model. The research question is important, because it increases awareness about the effects of regulation on personalized pricing in the European union internal market.
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(2024)Opportunistic insurance fraud has been given little attention in academic studies, even though it is estimated to account for the majority of insurance fraud. This global phenomenon distorts insurance markets, leading to higher premium prices for honest consumers. The motivation for this thesis is to gain deeper understanding of opportunistic insurance fraud, its causes, and to provide possible solutions to tackle it. This thesis provides a comprehensive literature review, combined with two theoretical models to study opportunistic insurance fraud. The first model introduced is the costly state verification model with two different auditing strategies. This model is used to find optimal insurance contracts under asymmetry. The second model is the fraud triangle with three elements: motivation, opportunity, and rationalization. In sum, the fraud triangle model explains opportunistic insurance fraud. The results from this analysis support the concept of a rational, utility maximizing consumer, whose main motivation for fraud is money. Opportunity is provided by the industry itself due to inadequate measures of detection and prevention. In addition, societal norms indicate a strong acceptance of fraudulent behavior, which is often seen as a victimless crime.
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(2022)The opportunity costs of defence and the impact of defence spending on economic growth aroused the interest of researchers during the Cold War. The question is topical again, as the war in Ukraine has accelerated international armaments and increased investments in defence. For Finland and Sweden, the issue is also important in terms of future NATO membership, because NATO recommends that its member countries spend at least 2% of GDP on defence. Achieving the limit requires an increase in defence spending from both countries. No case studies on the impact of defence spending on economic growth have been published about Finland and Sweden, but the countries have been discussed as part of broader panel materials. This thesis fills the gap. The thesis applies structural vector autoregressive methods to analyse the period from 1960 to 2021. Granger causality is included in the analysis, because–despite its problematic nature–the concept has a central position in the history of the research topic. Previous literature has considered the identification of a structural model challenging because the determination of bidirectional causality would require a suitable exogenous variable, which is almost impossible to find in this context. The view is challenged by suggesting that a partial identification can be accepted when the interest is focused only on the defence spending shock. The alternative analysis concerning a shorter time period tests the sensitivity of results to a time period. The impulse response analysis suggests that the impact of defence spending on GDP is slightly positive for both countries, but statistically significant only for Sweden. Granger causality is not observed in either direction for either country. Finland's neutral result is in line with expectations and previous literature, but Sweden's positive result is contrary to expectations. The alternative analysis concerning the post-Cold War era confirms that the Finnish result is robust regardless of the time period. The inconsistency with previous literature and the challenges caused by conditional heteroskedasticity raise doubts about the reliability of the Swedish result. The thesis indicates that increases in defence spending will not harm economic growth in Finland and Sweden. The result is surprising, as it has been suggested that previous studies have underestimated the negative impact of defence spending and most of the recent literature supports a negative or neutral impact. Further research is needed, especially on the impact mechanisms and the causes of heterogeneity. Decomposing defence spending could provide answers to unresolved questions.
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(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.
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(2022)The Finnish productivity growth has been sluggish in the period after the great financial crisis. According to Schumpeterian growth theory, produc- tivity growth depends on innovation and competition between firms. In the United States, the productivity slowdown that has occurred during recent decades has been linked to the simultaneous decline in business dynamism. Therefore, this thesis investigates the Finnish competition and business dy- namism in the period between 2004 and 2018, using dynamic and static competition indicators. The main data sources of this work are two micro-aggregated databases developed by the OECD. Due to their high level of harmonization, a compar- ison between Finland and a benchmark group of countries is possible. The work presents descriptive results and then investigates the relationship be- tween the different indicators with fixed effects regression models. The work finds that, when measured with dynamic indicators (entry rates, up or out dy- namics, and job reallocation rates), the level industry dynamism in Finland is as high, or even higher than in the benchmark. Regarding the static indica- tors of competition, industry concentration appears to be higher than in the benchmark, and has increased in the recent years. However, concentration is not linked to increases in mark-ups or entry rate decline. Instead, it can be linked to the reallocation of resources to more productive firms. Nevertheless, allocative efficiency, as measured with Olley and Pakes covariance, is weaker than in the benchmark group of countries. However, low productivity disper- sion between firms may partly explain this. The results are mostly robust to earlier evidence on Finnish business dynamism. The study concludes that the state of competition and business dynamism in the Finnish private sector is good and thus does not seem to be the scape- goat for the productivity slowdown in Finland. However, the low levels of allocative efficiency and the factors behind it call for further investigation. Regarding markups, the results contract some results acquired earlier, and it would be interesting to compare different markup estimates, and study the relationship between the different estimates and innovation, concentration and productivity growth.
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