Testing Seasonal Unit Roots in Data at Any Frequency, an HEGY approach

This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.

A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion

Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.

Tillväxt som kontrovers : Ekonomers och sociologers debatt om den svenska offentliga sektorn

The controversy of growth: a debate between economists and sociologists about the Swedish public sector Has the ‘Swedish model’ forced Sweden into stagnating economic growth? And has this caused Sweden to lag behind other comparable OECD-countries from the 1970s and onwards, i.e. since Sweden chose a welfare path different from many other countries? This has been the subject of a more than twenty year long controversy between Walter Korpi, professor of sociology and social policy, and leading Swedish mainstream economists. In a series of articles, especially during the years of economic crisis in the 1990s, Walter Korpi claimed that other reasons than the Swedish model has to be taken into account when comparing welfare states and their impact on economic growth, while the economists have persistently maintained the opposite view. These disputes over statistics and methodology have developed into what is here referred to as a science based controversy. This article analyzes the controversy between sociology and economy in accordance with controversy theory. In this way we can consider both the underlying social as well as political aspects of the debate, which leads to the conclusion that not every aspect of a science-based controversy is a byproduct of science itself.

Kriskommunikation i ett heterogent samhälle : lika för alla eller till var och en efter behov?

The controversy of growth: a debate between economists and sociologists about the Swedish public sector Has the ‘Swedish model’ forced Sweden into stagnating economic growth? And has this caused Sweden to lag behind other comparable OECD-countries from the 1970s and onwards, i.e. since Sweden chose a welfare path different from many other countries? This has been the subject of a more than twenty year long controversy between Walter Korpi, professor of sociology and social policy, and leading Swedish mainstream economists. In a series of articles, especially during the years of economic crisis in the 1990s, Walter Korpi claimed that other reasons than the Swedish model has to be taken into account when comparing welfare states and their impact on economic growth, while the economists have persistently maintained the opposite view. These disputes over statistics and methodology have developed into what is here referred to as a science based controversy. This article analyzes the controversy between sociology and economy in accordance with controversy theory. In this way we can consider both the underlying social as well as political aspects of the debate, which leads to the conclusion that not every aspect of a science-based controversy is a byproduct of science itself.

Elevers läsvanor : En kvalitativ studie av fyra fordonselevers läsvanor

The following study was conducted at an upper secondary school in Sweden and attempts to explore the question of what influences male pupils’ reading habits. Many quantitative international studies, including PISA, PIRLS and IEA Reading Literacy, have sought to answer this question, but only partially succeeded due to the limitations of their methods. Therefore, this study seeks to explore this question in more depth using qualitative methods, including interviews and classroom observations, but also minor tests. Two facts which the previously mentioned international studies have found is that boys and particularly immigrant boys tend to have worse reading results than their counterparts. It is therefore the aim of this study to study four male students in upper secondary school; of which two are native Swedes and the other two are unaccompanied refugee children; one from Afghanistan and the other from Morocco. The findings of this study are as follows. Firstly, necessity was found to be the single most important factor for the reading habits of these four pupils; especially the two refugees. Both refugees learnt to read under harsh circumstances in madrassas in their respective home countries. Moreover, the Moroccan pupil learnt to speak and read Spanish fluently during his seven years as a homeless child. Furthermore, in the absence of necessity, interest was found to be decisive in determining the pupils’ reading habits. In addition to this, the study theorizes that an interest in reading generally arises before the ability to read and not vice versa. However, teachers can in fact affect their pupils’ reading habits even in upper secondary school.

Using Spatiotemporal Methods to Fill Gaps In Energy Usage Interval Data

Researchers analyzing spatiotemporal or panel data, which varies both in location and over time, often find that their data has holes or gaps. This thesis explores alternative methods for filling those gaps and also suggests a set of techniques for evaluating those gap-filling methods to determine which works best.

Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.

Robustness of stationary tests under long-memory alternatives

This paper investigates the presence of long memory in financiaI time series using four test statistics: V/S, KPSS, KS and modified R/S. There has been a large amount of study on the long memory behavior in economic and financiaI time series. However, there is still no consensus. We argue in this paper that spurious short-term memory may be found due to the incorrect use of data-dependent bandwidth to estimating the longrun variance. We propose a partially adaptive lag truncation procedure that is robust against the presence of long memory under the alternative hypothesis and revisit several economic and financiaI time series using the proposed bandwidth choice. Our results indicate the existence of spurious short memory in real exchange rates when Andrews' formula is employed, but long memory is detected when the proposed lag truncation procedure is used. Using stock market data, we also found short memory in returns and long memory in volatility.

O trabalho atrapalha os estudos?

Nas últimas décadas a frequência à escola entre os jovens brasileiros aumentou consideravelmente. A porcentagem de crianças, entre 10 e 14 anos de idade que estão matriculados na escola está acima de 95% e na faixa de 15 a 18 anos de idade, cerca de 70%. Vinte anos atrás estes números eram 80% e 50%, respectivamente. Por outro lado, quando se analisa os dados de participação na força de trabalho o quadro é menos otimista: para ambos os grupos, a participação é bastante elevada e tem apresentado comportamento estável ao longo dos anos. Este estuda analisa o efeito da participação no mercado de trabalho sobre o atraso escolar de crianças de nestes dois grupos de faixa etária utilizando a metodologia de emparelhamento por nota de propensão (propensity score matching) de participação no mercado de trabalho. Como seria de se esperar quanto maior a probabilidade de participar maior o atraso escolar. Mas, nosso principal resultado é que em ambos os grupos e mais acentuadamente para os mais jovens, a diferença de atraso entre os que participam e não participam do mercado de trabalho é mais elevado para valores intermediários de probabilidade de trabalhar. Nos valores extremos da distribuição as diferenças não são tão elevadas e muitas vezes não significantes estatisticamente. Isto significa que para os jovens com elevada probabilidade de participar no mercado de trabalho, e que são os que têm o mais elevado grau de atraso escolar, o trabalho em si não é a maior razão para este mal desempenho. Estes resultados sugerem que as políticas públicas para combate ao atraso escolar entre os grupos mais pobres deveriam ser mais abrangentes envolvendo uma ação mais ampla sobre a família e não apenas na erradicação do trabalho infantil e juvenil.

Pairs trading: uma aplicação ao mercado acionário brasileiro

Neste trabalho, verificamos viabilidade de aplicação da estratégia de pairs trading no mercado acionário brasileiro. Diferentemente de outros estudos do mesmo tema, construímos ativos sintéticos a partir de uma combinação linear de preços de ações. Conforme Burgeois e Minko (2005), utilizamos a metodologia de Johansen para a formação dos pares a serem testados. Após a identificação de pares cointegrados, para assegurar a estacionaridade do ativo sintético contruído a partir da relação linear de preços das ações, utilizamos os testes DF-GLS e KPSS e filtramos àqueles que apresentavam raiz unitária em sua série de tempo. A seguir, simulamos a estratégia (backtesting) com os pares selecionados e para encontrar os melhores parâmetros, testamos diferentes períodos de formação dos pares, de operação e de parâmetros de entrada, saída e stop-loss. A fim de realizarmos os testes de forma mais realista possível, incluímos os custos de corretagem, de emolumentos e de aluguel, além de adicionar um lag de um dia para a realização das operações

The importance of common cyclical features in VAR analysis: a Monte-Carlo study

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian inflation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in different measures of forecasting accuracy are substantial, especially for short horizons.

The importance of Common-Cyclical Features in VAR analysis: a Monte-Carlo study (Preliminary Version)

Despite the belief, supported byrecentapplied research, thataggregate datadisplay short-run comovement, there has been little discussion about the econometric consequences ofthese data “features.” W e use exhaustive M onte-Carlo simulations toinvestigate theimportance ofrestrictions implied by common-cyclicalfeatures for estimates and forecasts based on vectorautoregressive and errorcorrection models. First, weshowthatthe“best” empiricalmodeldevelopedwithoutcommoncycles restrictions neednotnestthe“best” modeldevelopedwiththoserestrictions, duetothe use ofinformation criteria forchoosingthe lagorderofthe twoalternative models. Second, weshowthatthecosts ofignoringcommon-cyclicalfeatures inV A R analysis may be high in terms offorecastingaccuracy and e¢ciency ofestimates ofvariance decomposition coe¢cients. A lthough these costs are more pronounced when the lag orderofV A R modelsareknown, theyarealsonon-trivialwhenitis selectedusingthe conventionaltoolsavailabletoappliedresearchers. T hird, we…ndthatifthedatahave common-cyclicalfeatures andtheresearcherwants touseaninformationcriterium to selectthelaglength, theH annan-Q uinn criterium is themostappropriate, sincethe A kaike and theSchwarz criteriahave atendency toover- and under-predictthe lag lengthrespectivelyinoursimulations.