Tuloverotuksen reaalinen muuttuminen Suomessa : Kuusikymmentä vuotta verojen vuoristorataa

The study seeks to find out whether the real burden of the personal taxation has increased or decreased. In order to determine this, we investigate how the same real income has been taxed in different years. Whenever the taxes for the same real income for a given year are higher than for the base year, the real tax burden has increased. If they are lower, the real tax burden has decreased. The study thus seeks to estimate how changes in the tax regulations affect the real tax burden. It should be kept in mind that the progression in the central government income tax schedule ensures that a real change in income will bring about a change in the tax ration. In case of inflation when the tax schedules are kept nominally the same will also increase the real tax burden. In calculations of the study it is assumed that the real income remains constant, so that we can get an unbiased measure of the effects of governmental actions in real terms. The main factors influencing the amount of income taxes an individual must pay are as follows: - Gross income (income subject to central and local government taxes). - Deductions from gross income and taxes calculated according to tax schedules. - The central government income tax schedule (progressive income taxation). - The rates for the local taxes and for social security payments (proportional taxation). In the study we investigate how much a certain group of taxpayers would have paid in taxes according to the actual tax regulations prevailing indifferent years if the income were kept constant in real terms. Other factors affecting tax liability are kept strictly unchanged (as constants). The resulting taxes, expressed in fixed prices, are then compared to the taxes levied in the base year (hypothetical taxation). The question we are addressing is thus how much taxes a certain group of taxpayers with the same socioeconomic characteristics would have paid on the same real income according to the actual tax regulations prevailing in different years. This has been suggested as the main way to measure real changes in taxation, although there are several alternative measures with essentially the same aim. Next an aggregate indicator of changes in income tax rates is constructed. It is designed to show how much the taxation of income has increased or reduced from one year to next year on average. The main question remains: How aggregation over all income levels should be performed? In order to determine the average real changes in the tax scales the difference functions (difference between actual and hypothetical taxation functions) were aggregated using taxable income as weights. Besides the difference functions, the relative changes in real taxes can be used as indicators of change. In this case the ratio between the taxes computed according to the new and the old situation indicates whether the taxation has become heavier or easier. The relative changes in tax scales can be described in a way similar to that used in describing the cost of living, or by means of price indices. For example, we can use Laspeyres´ price index formula for computing the ratio between taxes determined by the new tax scales and the old tax scales. The formula answers the question: How much more or less will be paid in taxes according to the new tax scales than according to the old ones when the real income situation corresponds to the old situation. In real terms the central government tax burden experienced a steady decline from its high post-war level up until the mid-1950s. The real tax burden then drifted upwards until the mid-1970s. The real level of taxation in 1975 was twice that of 1961. In the 1980s there was a steady phase due to the inflation corrections of tax schedules. In 1989 the tax schedule fell drastically and from the mid-1990s tax schedules have decreased the real tax burden significantly. Local tax rates have risen continuously from 10 percent in 1948 to nearly 19 percent in 2008. Deductions have lowered the real tax burden especially in recent years. Aggregate figures indicate how the tax ratio for the same real income has changed over the years according to the prevailing tax regulations. We call the tax ratio calculated in this manner the real income tax ratio. A change in the real income tax ratio depicts an increase or decrease in the real tax burden. The real income tax ratio declined after the war for some years. In the beginning of the 1960s it nearly doubled to mid-1970. From mid-1990s the real income tax ratio has fallen about 35 %.

Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

Kädestä suuhun : Makro- ja mikrotaloudellinen tarkastelu suomalaisten kotitalouksien säästämisestä ja sen mittaamisesta 1950-luvulla

This study is divided into two parts: a methodological part and a part which focuses on the saving of households. In the 1950 s both the concepts as well as the household surveys themselves went through a rapid change. The development of national accounts was motivated by the Keynesian theory and the 1940 s and 1950 s were an important time for the development of the national accounts. Before this, saving was understood as cash money or money deposited in bank accounts but the changes in this era led to the establishment of the modern saving concept. Separate from the development of national accounts, household surveys were established. Household surveys have been conducted in Finland from the beginning of the 20th century. At that time surveys were conducted in order to observe the working class living standard and as a result, these were based on the tradition of welfare studies. Also a motivation for undertaking the studies was to estimate weights for the consumer price index. A final reason underpinning the government s interest in observing this data regarded whether there were any reasons for the working class to become radicalised and therefore adopt revolutionary ideas. As the need for the economic analysis increased and the data requirements underlying the political decision making process also expanded, the two traditions and thus, the two data sources started to integrate. In the 1950s the household surveys were compiled distinctly from the national accounts and they were virtually unaffected by economic theory. The 1966 survey was the first study that was clearly motivated by national accounts and saving analysis. This study also covered the whole population rather than it being limited to just part of it. It is essential to note that the integration of these two traditions is still continuing. This recently took a big step forward as the Stiglitz, Sen and Fitoussi Committee Report was introduced and thus, the criticism of the current measure of welfare was taken seriously. The Stiglitz report emphasises that the focus in the measurement of welfare should be on the households and the macro as well as micro perspective should be included in the analysis. In this study the national accounts are applied to the household survey data from the years 1950-51, 1955-56 and 1959-60. The first two studies cover the working population of towns and market towns and the last survey covers the population of rural areas. The analysis is performed at three levels: macro economic level, meso level, i.e. at the level of different types of households, and micro level, i.e. at the level of individual households. As a result it analyses how the different households saved and consumed and how that changed during the 1950 s.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

A model Integrating the Facilities Management Process with the Building End User’s Business Process (ProFacil)

The ProFacil model is a generic process model defined as a framework model showing the links between the facilities management process and the building end user’s business process. The purpose of using the model is to support more detailed process modelling. The model has been developed using the IDEF0 modelling method. The ProFacil model describes business activities from the generalized point of view as management-, support-, and core processes and their relations. The model defines basic activities in the provision of a facility. Examples of these activities are “operate facilities”, “provide new facilities”, “provide re-build facilities”, “provide maintained facilities” and “perform dispose of facilities”. These are all generic activities providing a basis for a further specialisation of company specific FM activities and their tasks. A facilitator can establish a specialized process model using the ProFacil model and interacting with company experts to describe their company’s specific processes. These modelling seminars or interviews will be done in an informal way, supported by the high-level process model as a common reference.

The expiration day effect of indexoptions and index futures on the underlying shares

This paper studies the effect of the expiration day of index options and futures on the trading volume, variance and price of the underlying shares. The data consists of all trades for the underlying shares in the FOX-index for expiration days during the period October 1995 to the mid of yer 1999. The main results seem to support the findings of Kan 2001, i.e. no manipulation on a larger scale. However, some indication of manipulation could be found if certain characteristics are favorable. These characteristics include: a) a large quantity of outstanding futures or at/in the money options contracts, b) there exists shares with high index weight but fairly low trading volume. Lastly, there is some indication that manipulation might be more popular towards the end of the examined time period.

Monetary Policy, Stock Price Misalignments and Macroeconomic Instability

Perhaps the most fundamental prediction of financial theory is that the expected returns on financial assets are determined by the amount of risk contained in their payoffs. Assets with a riskier payoff pattern should provide higher expected returns than assets that are otherwise similar but provide payoffs that contain less risk. Financial theory also predicts that not all types of risks should be compensated with higher expected returns. It is well-known that the asset-specific risk can be diversified away, whereas the systematic component of risk that affects all assets remains even in large portfolios. Thus, the asset-specific risk that the investor can easily get rid of by diversification should not lead to higher expected returns, and only the shared movement of individual asset returns – the sensitivity of these assets to a set of systematic risk factors – should matter for asset pricing. It is within this framework that this thesis is situated. The first essay proposes a new systematic risk factor, hypothesized to be correlated with changes in investor risk aversion, which manages to explain a large fraction of the return variation in the cross-section of stock returns. The second and third essays investigate the pricing of asset-specific risk, uncorrelated with commonly used risk factors, in the cross-section of stock returns. The three essays mentioned above use stock market data from the U.S. The fourth essay presents a new total return stock market index for the Finnish stock market beginning from the opening of the Helsinki Stock Exchange in 1912 and ending in 1969 when other total return indices become available. Because a total return stock market index for the period prior to 1970 has not been available before, academics and stock market participants have not known the historical return that stock market investors in Finland could have achieved on their investments. The new stock market index presented in essay 4 makes it possible, for the first time, to calculate the historical average return on the Finnish stock market and to conduct further studies that require long time-series of data.

Pricing Index Options with Stochastic Volatility

The objective of this paper is to investigate the pricing accuracy under stochastic volatility where the volatility follows a square root process. The theoretical prices are compared with market price data (the German DAX index options market) by using two different techniques of parameter estimation, the method of moments and implicit estimation by inversion. Standard Black & Scholes pricing is used as a benchmark. The results indicate that the stochastic volatility model with parameters estimated by inversion using the available prices on the preceding day, is the most accurate pricing method of the three in this study and can be considered satisfactory. However, as the same model with parameters estimated using a rolling window (the method of moments) proved to be inferior to the benchmark, the importance of stable and correct estimation of the parameters is evident.