Nationalekonomisk litteratur har visat att utsatthet för skolmobbning kan ha negativa konsekvenser på lång sikt såsom lägre utbildningsnivå och löner. I denna uppsats undersöks huruvida olovlig frånvaro kan vara en mekanism som ligger till grund för de långsiktiga följderna genom att studeraorsakssambandet mellan mobbning och skolkning. Därtill undersöks ifall elevernas kön har en påverkan i denna fråga. OLS samt paneldatametoden fixed effects används i studien med hjälp av data på kommunnivå från finska enkätundersökningen Hälsa i skola för åren 2017 och 2019. I studien hittas inget starkt bevis för att mobbning skulle orsaka olovlig frånvaro hos offren eftersom den mest pålitliga modellen inte finner något signifikant samband. Dock tyder övriga resultat på att det kan finnas ett i verkligheten. Andra modeller estimerar att en procentenhets ökning i andelen mobbade elever orsakar ungefär 0,2 procentenheters ökning i andelen skolkande elever. Resultaten indikerar att det kan finnas könsskillnader i denna fråga. / It has been shown in the economical literature that being bullied at school may have negative consequences in the long run, such as lower educational levels and wages. This paper examines whether school absenteeism could possibly be one mechanism behind the long-run consequences by studying the causality between bullying and truancy. Gender’s role in the question has also been examined. OLS and panel data method fixed effects along with Finnish survey data for 2017 and 2019 are applied. No strong evidence that bullying would lead the victims to truant was found as the most reliable model couldn't find any significant association. Other results, though, suggest that such causality might exist. Alternative models estimate that a one percentage point increase in the share of students bullied causes an increase of approximately 0,2 percentage points in the share of truants. The results indicate that there might be gender differences regarding the topic.

Inflationen har i många länder varit låg sedan finanskrisen 2008. I försök öka inflationstakten har centralbanker sänkt sina räntor till rekordlåga nivåer. I Danmark, Schweiz och Sverige har styrräntorna varit negativa. John B Taylor föreslog 1993 en makroekonomisk regel med syfte att kunna ge en prognos för styrräntan. Enligt Taylorregeln kan styrräntan förklaras av tidigare perioders inflationstakt och bruttonationalprodukt. Denna uppsats syftar till att undersöka Taylorregelns empiriska relevans i Danmark, Schweiz och Sverige under perioden 2000 till 2018. Två tester genomförs. Det första är att, med en linjär regressionsmodell, undersöka sambandet mellan styrränta, inflationsgap och BNP-gap. Det andra är ett Granger-kausalitetstest för att se om den implicerade kausaliteten i Taylorregeln stämmer. Granger-testet bygger på resultaten från en vektor autoregression. Resultaten i denna uppsats visar att det finns ett samband mellan inflationstakt och styrränta, men inte mellan BNP-gap och styrränta i de valda länderna under undersökningsperioden. Vidare visar resultaten att kausaliteten går från inflationsgap och BNP-gap mot styrränta, som Taylorregeln föreslår. Resultatet lyckas inte påvisa att negativa styrräntor skulle påverka Taylorregelns relevans. / The rate of inflation has been low in many countries since the financial crisis in 2008. In attempts to increase the inflation rate, central banks have lowered their interest rates to historically low levels. In Denmark, Switzerland and Sweden, the central banks key interest rates have been negative. In 1993, John B Taylor proposed a macroeconomic rule with the aim of providing a forecast for the key interest rate. According to the Taylor rule, the policy rate can be explained by the inflation rate and gross domestic product of previous periods. This paper aims to investigate the empirical relevance of the Taylor rule in Denmark, Switzerland and Sweden during the period 2000 to 2018. To do this, two tests are performed. The first is that, with a linear regression model, investigate the relationship between the key interest rate, the inflation gap and the GDP gap. The second is a Granger causality test to see if the implicit causality of the Taylor rule is correct. The Granger test is based on the results of a vector autoregression. The results of this paper show that there is a correlation between the rate of inflation and the key interest rate, but not between the GDP gap and the key interest rate in the selected countries during the investigation period. Furthermore, the results show that causality goes from the inflation gap and the GDP gap towards the key interest rate, as the Taylor rule suggests. The result does not suggest that negative key interest rates would affect the relevance of the Taylor rule.

Panel data analysis is the modern approach of statistical and econometric modeling. The aim of the thesis is to estimate the gravity model of international trade in alcoholic beverages in the form of bilateral trade flow depending on the gross domestic product and other associated variables that facilitate trading. The data have a panel structure. Based on the results of panel unit root tests the stationarity of variables in the panel and the expected long-term relationship between the analyzed variables are tested. Gravity model is assuming the existence of long-term relationships built through various methods, such as pooling OLS estimate, fixed and random effects models, cointegrated regression DOLS and FMOLS. Cointegration relationship is verified by Pedroni panel test.

Denna uppsats försöker identifiera faktorer som förklarar varför cykelpendlingen till och från Stockholms innerstad har ökat mellan 1980 och 2020. Vi bildar och väljer ut tre linjära regressionsmodellerna vilka vi anser vara de bästa modellerna utifrån ett flertal urvalskriterier. Resultaten visar att alla inkluderade variabler är signifikanta i respektive modell. Våra resultat, vilka är i linje med tidigare forskning, visar vidare följande: (a) antalet cykelpendlingsresor har ett positivt samband med cykelinfrastrukturkostnader, vilket tyder på att bättre cykelinfrastruktur gör att fler väljer cykeln till jobbet; (b) antalet cykelpendlingsresor har ett positivt samband med befolkningsstorleken; (c) antalet cykelpendlingsresor har ett positivt samband med trängselskatten, vilket tyder på att en överföring sker där en del bilister byter till cykelpendling p.g.a. trängselskatt; (d) antalet cykelpendlingsresor har ett negativt samband med BNP per capita. Sammanfattningsvis indikerar resultaten att ett flertal faktorer har påverkat antalet cykelpendlingsresor till och från Stockholms innerstad mellan 1980 och 2020. / This thesis attempts to identify factors that explain why bicycle commuting in and out of Stockholm City Centre has increased between the years 1980 and 2020. We create and select three linear regression models, which we consider to be the best models based on several selection criteria. Our results show that the included variables in each respective model are significant. Our results, which are in line with previous findings in the literature, moreover, show the following: (a) the number of bicycle commuting trips is positively associated with bicycle infrastructure costs, which indicates that better bicycle infrastructure leads to more people bicycling to work; (b) the number of bicycle commuting trips is positively associated with population size; (c) the number of bicycle commuting trips is positively associated with the congestion tax, which indicates that a modal shift takes place where some motorists switch to bicycle commuting because of the congestion tax; (d) the number of bicycle commuting trips is negatively associated with GDP per capita. In summary, the results indicate that several factors have affected the number of commuting trips by bicycle in and out of Stockholm City Centre between 1980 and 2020.

The boundaries of the cities are not immutable, they can be changed. With the development of the economies and societies, the population and pollution of cities are increasing. Some urban areas are expanding with more population or other dynamics of urbanization, while other urban areas are reducing with the changing of the dynamics. Therefore, detecting urban areas or delineating the boundaries of the cities is one of the most important steps for urban studies, which is closely related to human settlements and human activities. Remote sensing data (RS) is widely used to monitor and detect land use and land cover on the surface of the earth. But the extraction of urban areas from the ordinary RS data is not easy work. The Operational Linescan System (OLS) is the sensors of the Defense Meteorological Satellite Program (DMSP). The nighttime lights from the DMSP/OLS provide worldwide remotely sensed data to analyze long-term light emissions which are closely related to human activities. But the nighttime lights imagery data contains inherent errors. Therefore, the approaches to calibrate the data and extract the urban areas from the data are complicated. The long-term objective of this thesis is to delineate the boundaries of the natural cities of the continental United States of America (USA) from 1992 to 2010 of nightlight imagery data with all the different satellites. In this thesis, the coefficients for the intercalibration of the nightlight imagery data have been calculated based on the method developed by Elvidge, et al. (2009), but the coefficients are new and available. The approach used to determine the most appropriate threshold value is very important to eliminate the possible data error. The method to offset this possible error and delineate the boundaries of the cities from nightlight imagery data is the head/tail breaks classification, which is proposed by Jiang (2012b). The head/tail breaks classification is also useful for finding the ht-index of the extracted natural cities which is developed by Jiang and Yin (2013). The ht-index is an indicator of the underlying hierarchy of the data. The results of this study can be divided into two categories. In the first, the achieved coefficients for the intercalibration of nightlight images of the continental USA are shown in a table, and the achieved data of the urban areas are stored in a data archive. In the second, the different threshold values of the uncalibrated images and the individual threshold value of the calibrated images are shown in tables, and the results of the head/tail breaks classification and power law test are also drawn. The results show that the acquired natural cities obey the power law distribution. And the results also confirm that the head/tail breaks classification is available for finding a suitable threshold value for the nightlight imagery data. Key words: cities’ boundaries; DMSP/OLS; head/tail breaks classification; nighttime lights; power law; urban areas

Although it remains a tea consuming nation, both production and consumption of coffee in China has been increasing at double-digit rates and is not expected to slow down (International Coffee Organization (ICO), 2015). With investments and upward trends in production and rapid increases in consumption of coffee in China it is important for producers and retailers of the bean1 in China to understand the new Chinese coffee consumer. Using survey data from Wuhan, China we help understand the Chinese coffee consumer by explaining their consumption using standard OLS regression. Results show that whether or not consumers make/brew their own coffee, how long consumers have been consuming coffee regularly, the size of the coffee cup most often purchased and individuals’ prediction of their coffee consumption in the following year are all important in explaining Chinese coffee consumption. We suggest for long-run success, that Chinese coffee producers and retailers in China focus on the quality of their coffee bean. 1 ‘bean’ refers to coffee

Over the past three decades, economic reforms have brought about dramatic changes in China. The wave of structural and economic reforms regarding the State-owned Sector (SOS), and the surge of the Non-State-owned Sector (NSOS), have influenced returns in the labor market, such as the returns concerning human capital and political capital in urban China. Presumably, the NSOS would be more marketed-oriented compared to the SOS, and it would have different returns concerning political capital, as represented by Chinese Communist Party (CCP) membership. This is likely because the NSOS would not value Party membership as much as the SOS does. The question of how Party membership is rewarded in the two sectors might also change with the development of the two ownership sectors, as more time passes since the establishment of the economic reforms. I examine whether CCP members display any earnings advantage in these two sectors, and I also explore how such an advantage might have changed over time. Unlike most of the previous studies that have focused on earnings in urban China, I treat Party membership affiliation and ownership sector selection as being endogeneous. I apply the Mlogit -OLS two-stage selection correction estimation proposed by Lee (1983) and discover evidence which suggests that Party membership serves as a proxy for both political and productive skills. A flat Party premium in the SOS and a decreasing Party premium in the NSOS suggest that the Party card served a similar function in the payment scheme present in the SOS during this three year span, whereas the NSOS valued political capital by a decreasing amount over time. The evidence presented in my dissertation indicates that economic reforms tend to mitigate the earning advantage of Party members that occurs as a result of unequal treatment based on Party membership. This evidence suggests that CCP membership is losing its earning power, at least in the NSOS. In addition, the CCP members sacrifice the benefits previously possessed in the adaptation to the transformed economic environment in urban China. However, the rewards to other forms of human capital have increased over time.

The objective of this study is to estimate advertising effects on international tourismdemand for the leading Swedish winter destination, Åre. The increasing share of foreigninbound tourists in this destination region creates a strong interest by shareholders toidentify the factors responsible for this trend. According to traditional micro-economictheory, economic factors, such as income and price, are considered as main determinantsfor tourism demand (Song and Witt 2000). However, according to advertising theories(Comanor and Wilson, 1974) and previous tourism research (Bhagwat and Debruine, 2008;Divisekera and Kulendran, 2006), this study additionally focuses on the brand awarenessof Åre as perceived by international tourists. More concretely, advertising theoriesdistinguish between the brand and the information function of advertising (Nelson, 1974).The former function follows the idea that advertising increases the level of productdifferentiation to build up a base of loyal customers. By contrast, the information functionimplies that advertising primarily provides information about products in order to increasethe market transparency. Accordingly, in order to estimate the impact of advertisingexpenditures for off- and online channels as well as promotional activities, furtherexplanatory variables, e.g. mega events, are considered in this study (Salman, 2003; Songet al., 2010). By applying ordinary least square (OLS) methods, demand elasticitycoefficients are estimated for each of the sending countries Norway, Finland, Russia,Denmark and the UK. Results show that advertising is the main significant driver oftourism demand from the UK, Russia and Finland, while a comparably weak advertisingleverage can be shown for Denmark and Norway. Interestingly, in contrast to microeconomictheories tested in previous research, income and tourism price levels reveal asbeing less significant drivers for demand in all analysed tourism markets. In turn, theresults provide evidence that the increased usage of online channels most significantlyaffects consumers’ buying behaviour. Finally, with respect to brand image perception,results reveal that the destination of Åre is perceived as a brand by tourists from Denmark.Moreover, for customers from the countries Norway and Finland, Åre indicates a weakbrand perception, while tourists from Russia and the UK don’t perceive Åre as a brand atall. The results gained by this research conducted at the level of the tourism destinationprovide useful hints about the factors influencing travel behaviour of tourists from maininternational markets. The study supports destination managers to appropriately adjustmarketing campaigns according to the predominant level of brand perception in respectivesending countries. / KK-Foundation project ‘Engineering the Knowledge Destination’ (no. 20100260; Stockholm, Sweden).

This paper examines the Environmental Kuznets Curve (EKC) hypothesis and tests for causality using Dynamic Ordinary Least Squares (DOLS) and the Vector Error Correction Model (VECM). There is evidence of long-run relationships in the three models under consideration. The Dynamic Ordinary Least Squares (DOLS) finds no evidence to support the existence of an environmental Kuznets curve (EKC) hypothesis for Zambia in the long-run. The evidence from the long-run suggests an opposite of the Environmental Kuznets Curve (EKC), in that the results indicate a U-shaped curve relationship between income and carbon emission. The conclusion on causality based on the VECM is that there is evidence of neutrality hypothesis between either total electricity and income or between industrial electricity and income in the short-run Additionally, there is evidence of conservation hypothesis in the context of residential and agricultural electricity consumption.

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