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Browsing by study line "General track"

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  • Virtanen, Emil (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.
  • Vesala, Lauri (2023)
    Carbon pricing is a cost-effective instrument of climate change mitigation policy. Its implementation is, however, limited by various political constraints. The goal of this thesis is to examine what factors empirically explain cross-country variation in carbon pricing policy. Understanding the political constraints limiting carbon pricing may have implications for policy design. Previous literature on the empirical determinants of carbon pricing policy has focused mostly on determinants based on political economy theory, such as variation in domestic interests, and been conducted with data only on explicit carbon pricing. Implicit carbon prices created by fuel excise taxes are, however, a significant part of the total price on emissions. This thesis contributes to existing literature by introducing two new determinants in public finance considerations and country-level social cost of carbon as well as utilizing broader carbon pricing data. Empirical methods used include regression based on maximum-likelihood estimation of censored data and multiple linear regression. The size of the public sector is found to have a statistically significant positive association with carbon pricing regardless of the model used. This supports the hypothesis that cross-country variation in carbon pricing is empirically explained by a need to finance public spending and by the double-dividend hypothesis. Other factors that are found to have a clear positive association with carbon pricing are level of democracy, administrative capacity, and GDP per capita. The results are somewhat mixed concerning the effect of other political institutions related factors as well as factors related to carbon intensity. The hypothesis that country-level social cost of carbon positively affects carbon pricing is clearly rebuked which suggests that a competitive game does not describe national-level policymakers’ decision-making. The results of the thesis should not, however, be interpreted as causal because of omitted variable bias, reverse causality, and a lack of time-series data.
  • Liukkonen, Sini (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 (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.
  • Suihkonen, Sini (2023)
    The importance of protecting sensitive data from information breaches has increased in recent years due to companies and other institutions gathering massive datasets about their customers, including personally identifiable information. Differential privacy is one of the state-of-the-art methods for providing provable privacy to these datasets, protecting them from adversarial attacks. This thesis focuses on studying existing differentially private random forest (DPRF) algorithms, comparing them, and constructing a version of the DPRF algorithm based on these algorithms. Twelve articles from the late 2000s to 2022, each implementing a version of the DPRF algorithm, are included in the review of previous work. The created algorithm, called DPRF_thesis , uses a privatized median as a method for splitting internal nodes of the decision trees. The class counts of the leaf-nodes are made with the exponential mechanism. Tests on the DPRF_thesis algorithm were run on three binary classification UCI datasets, and the accuracy results were mostly comparable with the two existing DPRF algorithms DPRF_thesis was compared to. ACM Computing Classification System (CCS): Computing methodologies → Machine learning → Machine learning approaches → Classification and regression trees Security and privacy → Database and storage security → Data anonymization and sanitization
  • Kaur, Anmol (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
  • Simi, Antti (2024)
    The goal of this thesis is to analyse what are the effects of the monetary policy conducted by the European Central Bank (ECB) on Finnish macroeconomy and how persistent those effects are. The thesis assumes that because Finland contributes only a very small fraction of the economic output of the euro area, the overall economic situation of Finland does not matter from the point of view of ECB when setting the monetary policy stand for the monetary union. Based on the notation that the ECB’s monetary policy can be considered exogenous, the effects of monetary policy are estimated in the thesis by Ordinary Least Squares (OLS), while using macroeconomic variables in euro area as covariates. By including the variables that express the overall economic status of the euro area, the analysis attempts to remove the systematic part of the monetary policy when estimating the effects of monetary policy. The data used for the modelling consists of main macroeconomic variables in euro area and Finland between 1999 and 2023. These are unemployment, industrial output, inflation and the short interest rate. The interest rate variable consists of two elements. Because for a timespan of several years interest rates were stuck at zero a shadow rate is used to represent the monetary policy stand of the central bank. During the time when the zero lower bound was not binding, 1-month Euribor is used as the interest rate variable. The modelling results are quite well in line with common understanding about the nature of the monetary policy and its effects on real economy. Increase in interest rates results in increase in unemployment, fall in industrial output and decrease in inflation. There were however some uncertainties with the results when considering higher confidence levels. Overall, the results of the thesis seem to be coherent with commonly hold views about the effects of the monetary policy. The chosen empirical approach seems to yield similar results as more commonly used SVAR and DGSE models. The conclusion of thesis is that the monetary policy does impact the real economic activity as is expected.
  • Vainikka, Assi (2023)
    This study examines the relationship between wealth and environmental contributions at individual and country levels by using survey data from EVS, WVS and ISSP and panel data from OECD. For the analysis I use correlation tests, and in the case of panel data, pooled OLS regression and two-way fixed effects regression, and with survey data I use OLS regression and generalized ordered logit model. The aim of this study is to clarify if wealthier countries or individuals contribute more to environment than countries and individuals with lower wealth. Environmental contributions at country level are measured as environmental policy stringency, environmental protection expenditure and environmentally related tax revenues. At individual level environmental contributions are measured as willingness to pay for environmental protection. At country level a positive relationship between wealth and environmental contributions is found, but in individual level the relationship is weak. Also relationship between national wealth and individual willingness to pay is minor. On average individuals willingness to pay for environmental protection stayed standard regardless of wealth, but some differences in averages can be seen comparing the results of different surveys. Results suggests that in wealthier countries the environmental policy is more strict and environmental protection expenditure can be expect to be higher than in lower GDP per capita level countries. The relationship between wealth and environmentally related tax revenues differs from other two variables, because tax base for environmentally related taxes change whit economic development. Previous literature offers inconclusive findings and comprehensive theoretical framework is difficult to form. One of the biggest challenges of this study is the sparseness of suitable and comparable data and thus, results have to be interpreted with caution.
  • Rönkkö, Niko-Petteri (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 (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 (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 (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 (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 (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.
  • Raikamo, Joackim (2022)
    Producing timely information regarding the current and future state of the economy is important for the practice of economic policy: the delay between the implementation of policy measures and the emergence of their effects is typically considerable, which creates a need to anticipate developments in macroeconomic variables. The producer price index is one such variable: producer price indices are used to track changes in the general price level of goods produced within an economy from the point-of-view of producers, which makes them prominent indicators of inflationary pressures and business cycle conditions. The principal objective of this thesis is to investigate whether the Finnish Producer Price Index for Manufactured Goods could be reliably forecasted in the short run using large sets of external predictors. Increasing the number of predictors exposes standard forecasting methods to inaccuracies and makes their application outright infeasible once the number of variables exceeds the number of observations available for the estimation of the forecasting model. Various alternative methods have been proposed to counter this issue. This thesis provides a broad overview of these methods as well as other relevant issues pertaining to the forecasting macroeconomic variables. Given that no single framework has proven to dominate others in practical applications, a selection of methods has been chosen for the empirical section of this thesis. These methods represent two different approaches to high-dimensional forecasting: dynamic factor models and penalized regressions. The effectiveness of dynamic factor models is based on the assumption that relevant information contained in high-dimensional data can be summarized using only relatively few underlying factors, the estimates of which can, in turn, be used for forecasting. The solution offered by penalized regressions, on the other hand, is based on striking a balance between the bias and variance of the forecasts. Out of the broader class of penalized methods, four different variations will be utilized in this thesis: the Ridge, Lasso, Elastic Net, and Adaptive Lasso. The empirical performance of the methods will be assessed by conducting a simulated out-of-sample forecasting experiment, in which a series of consecutive forecasts are estimated for the target variable using historical data. These forecasts are, in turn, compared to their realized counterparts. The objective of the experimental arrangement is to produce representative information regarding the empirical accuracy of the respective forecasting models by emulating circumstances faced in real-time forecasting: only information that would have been available at the time is used to produce each forecast. The set of predictors used in the experiment is composed of monthly economic time series collected from a variety of sources. Based on the forecasting experiment, the benefit of the high-dimensional models in terms of average forecasting accuracy turns out to be only marginal in comparison to a univariate autoregressive benchmark at the one-, two-, and three-month horizons. Moreover, the differences among the respective high-dimensional methods are found to be insignificant. On the other hand, more favorable results are achieved by using relatively timely market-based variables to predict the concurrent rather than strictly future values of the index. In this case, the penalized models perform particularly well. The results indicate that leveraging the advantage in publication lag enjoyed by external predictors for the purpose of contemporaneous prediction, or nowcasting, could represent the most potential for predicting the producer price index.
  • Kashfia, Ishrat Jahan (2024)
    Corruption poses a significant threat to political and economic stability in many developing and least-developed countries. There is increasing research exploring gender differences and attitudes towards corruption. While literature suggests that men tend to be more corrupt than women, the thesis investigates whether it holds true in the case of Uganda. Eight rounds of the Afrobarometer Survey, conducted in Uganda from 2002 to 2022, have been utilised to explore the gender difference in the engagement in bribery, a proxy used to capture corruption, with the help of a linear probability model. The results show that women are less likely to engage in bribery and the association is statistically significant while controlling for various demographic and political characteristics as well as round and region-specific fixed effects. However, this difference may be due to the gender difference in corruption perception. Even though the gender gap is persistent across all rounds, involvement in bribery has been increasing over time for both men and women. There are several limitations of the study, and further research is required to verify the gender gap as bribery involvement does not explain the other aspects of corruption. Future research can explore the Afrobarometer Survey even further and repeat the analysis for other African nations. Additionally, the datasets can be compiled together to assess the statistical significance of the gender gap in the presence of country-specific fixed effects. Furthermore, it is worth exploring the motivation behind involvement in bribery along with individual characteristics, such as degree of risk aversion, belief about oneself, and personality traits.
  • Ropa, Anton (2020)
    Työn tuottavuuden merkitys kansantalouden tasolla talouskasvulle ja mikrotaloustasolla yritysten tapauksessa niiden menestymiselle on merkittävä. Työn tuottavuuteen vaikuttavien tekijöiden kirjo on laaja ja tässä tutkielmassa keskitytään tarkastelemaan henkisen pääoman vaikutusta työn tuottavuuteen. Tarkastelun keskiössä on keinot henkisen pääoman konvertoimiseksi henkilöstötuottavuudeksi ja henkilöstötuottavuuden tilan mallintamiseksi. Tutkimuskysymyksenä tarkastellaan suomalaisten yritysten kannattavuuden ja henkilöstötuottavuusindeksin korrelaatiota. Henkisen pääoman olemassaolo ei ole tae yrityksen menestymiselle. Keskeistä henkilöstötuottavuuden kannalta on ottaa yrityksen omaama henkinen pääoma hyötykäyttöön. Haasteelliseksi tilanteen tekee se, että henkinen pääoma on sidoksissa yrityksen henkilöstöön. Tutkielmassa esiteltävän aiemman kirjallisuuden mukaan henkilöstötuottavuuden stimuloimisessa johtamiskäytänteet ja toimintatavat työyhteisöissä ovat mahdollisia keinoja vaikuttaa henkilöstötuottavuuden kehittymiseen työyhteisössä. Tutkielmassa henkilöstötuottavuutta kuvataan henkilöstötuottavuusindeksin (HTI) avulla. Menetelmä perustuu Ossi Auran ja muun tutkimusryhmän kehittämään malliin kuvata työyhteisön henkilöstötuottavuuden tilaa. Mallin keskeisiä piirteitä on jaotella henkilöstötuottavuus kolmen osatekijän summaksi: motivaatio, osaaminen ja työkyky. Tiedonkeruumenetelmänä henkilöstötuottavuusindeksin laskemiseksi toimii työyhteisöiden tilaa kuvaavien työyhteisökyselyiden hyödyntäminen. Yritysten taloudellista tilaa tarkastellaan tilinpäätöstietojen perusteella ja kannattavuuden indikaattorina toimii yrityksen käyttökateprosentti. Tutkimusmenetelmänä toimii pitkittäinen tutkimus. Aineisto on kerätty Työeläkeyhtiö Elon asiakkaille tarkoitetun työyhteisökyselyn avulla siten, että aineistoon valittu yritys on suorittanut vähintään kahdesti. Henkilöstötuottavuusindeksin ja yritysten taloudellisen tilanteen yhteyttä tarkastellaan lineaarista regressiomallia hyödyntäen. Empiirisessä osiossa tarkastelun kohteena on henkilöstötuottavuusindeksin ja yritystoiminnan kannattavuuden sekä henkilöstötuottavuusindeksin ja yritystoiminnan kasvun yhteys. Kannattavuuden muutosta kuvataan sekä käyttökateprosentin prosenttiyksiköittäisen että prosentuaalisen muutoksen avulla. Liiketoiminnan kasvua kuvataan liikevaihtoprosentin prosentuaalisen muutoksen avulla. Lineaarisen regressiomallin tuloksia tarkastellaan koko aineiston tasolla sekä osajoukkojen osalta valittujen määrittävien tekijöiden osalta. Tutkielman empiirisen osion tuloksien mukaan HTI:n muutoksien osalta, motivaatio on tärkein kolmesta osatekijästä. Itse tutkimuskysymyksen osalta saavutetut tulokset osoittavat, että henkilöstötuottavuuden ja yritysten kannattavuuden välillä ei havaita selkeää yhteyttä. Yhteyttä ei ole havaittavissa myöskään henkilöstötuottavuusindeksin ja liiketoiminnan kasvun väliltä. Tutkielman empiirinen osuus antaa hyvin perspektiiviä tutkittavaan ilmiöön ja antaa syytä aiempien tutkimusten tulosten kriittiselle tarkastelulle. Henkilöstötuottavuusindeksin muutoksien osalta motivaatio on tärkein kolmesta osatekijästä.
  • Lohikainen, Ossi (2022)
    Labor market effects of military service have been a popular topic for economic research, and in a subset of these studies, interactions with elements like race, parental socioeconomic status, and ability have been submitted as considerations. Introducing an Mincer-type empirical model for framing the problem, I undertake a literature survey of studies concerning themselves with such treatment effect heterogeneities, complemented by a brief empirical survey using CPS data. It is found that, whether the overall effect of service is positive or negative, comparatively gains/non-losses in earnings and education tend to accrue to the disadvantaged individuals over advantaged ones. The plurality of studies correspondingly find positive-to-neutral effects along this gradient, although neutral-to-negative findings are also featured. The contexts under study commonly involve notable influence from educational subsidies and draft deferment incentives, but there are some counterfactuals, which however are unable to establish a definite causal mechanism between service and earnings or education. The main findings of the paper should be considered in making adjustments to existing compulsory service policies.
  • Viitaharju, Olli-Pekka (2020)
    Finanssikriisin seurauksena keskuspankkien rahapolitiikan liikkumavara on vähentynyt, mikä on johtanut vaihtoehtoisten rahapolitiikan strategioiden harkitsemiseen. Yksi ehdotetuista strategioista on siirtyminen hintatasotavoitteeseen. Hintatasotavoitteessa keskuspankki pyrkii pitämään hintojen kehityksen valitsemallaan tavoiteuralla ja korjaa inflaatiotavoitteesta poiketen menneiden shokkien aikaansaamat poikkeamat. Tutkielmassa tarkastellaan viimeaikaista tutkimusta hintatasotavoitteseen liittyen ja selvitetään voisiko hintatasotavoite olla parempi rahapolitiikan strategia kuin inflaatiotavoite. Tarkastelun keskiössä ovat hintatasotavoitteen vahvat oletukset, mahdolliset edut ja siirtymän riskit. Tutkimusmenetelmänä on kirjallisuuskatsaus ja tavoitteena on muodostaa kokonaiskuva tutkimuksesta ja selvittää mihin jatkotutkimus pitäisi suunnata. Hintatasotavoitteen mahdollisia etuja ovat hintojen pitkän aikavälin ennustettavuus, inflaation ja tuotannon volatiliteetin vähentyminen sekä parempi suoriutuminen nollakorkorajalla. Edut voivat olla haastavia saavuttaa ja ne nojaavat vahvoihin oletuksiin inflaatio-odotuksien muodostumisesta uuskeynesiläisen mallin mukaan sekä keskuspankin kyvystä sitoutua siihen strategiana. Hintatasotavoitteeseen siirtymiseen liittyy paljon riskejä ja kustannuksia, joiden seurauksena nettovaikutus voi olla negatiivinen. Talouden toimijat eivät välttämättä sisäistä uutta strategiaa, jolloin vaikutus inflaatio-odotuksiin jää vaimeaksi. Lisäksi se saattaa aiheuttaa haasteita keskuspankin kommunikaatiolle ja uskottavuuden ylläpitämiselle. Hintatasotavoite suoriutuu teoriassa inflaatiotavoitetta paremmin, mutta tulokset ovat malliriippuvaisia ja usein ristiriitaisia keskenään. Lisätutkimuksen tarpeet liittyvät inflaatio-odotuksien muodostumiseen, oppimisvaiheen kestoon ja keskuspankin uskottavuuden ylläpitämiseen. Keskuspankit näkevät hintatasotavoitteen riskit edelleen merkittävinä ja siirtymä olisi monella tapaa hyppy tuntemattomaan.
  • Koski, Maaria (2019)
    The measured gross domestic product, GDP, does not consider non-paid homework in its figures. However, the relative size of the so called household production is large both from time use perspective but also as monetary wise. According to Statistics Finland, the non-salaried homework was 39.8 % of the measured Finnish GDP in 2016. Moreover, Finns spent on average three hours and 21 minutes on daily basis on household production in 2009. Yet, the standard economic theory also excludes household production in the models although individuals are known to allocate their time between market work, homework and leisure. The real business cycle theory attempts to explain and study the properties of business cycles. In this Master’s Thesis, the household production is studied within the real business cycle (RBC) theory. The purpose is to compare the benefits of including household production into the real business cycle model to the standard alternative where it is excluded. Real business cycles are studied by constituting a dynamic stochastic general equilibrium model (DSGE) for both cases: one for the household production and one for the standard non-household production. The models constituted are for a frictionless closed economy. Both models are then calibrated with Finnish figures and simulated. The results indicate that market hours are procyclical in both models. However, the correlation between output and market hours is 1.33 times larger in the household production model than in the standard model. Also, the household production model generates highly countercyclical home hours. Yet, the Finnish time use data cannot prove the procyclicality of household production hours. The main reason is that the time use research is conducted only every ten years. Also, the timing of the research does not reconcile with the Finnish recessions. Hence, the data available cannot explain the countercyclical home hours indicated by the household production real business cycle model. In this sense, the results presented can only be taken as describing facts of the Finnish economy when household production is considered.