This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. A penalized least squares estimation is linked to the GLS (Aitken) estimates of the corresponding linear model with time-invariant parameters. The VC estimates are moments...

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. This estimator does not require that disturbances are normally distributed, but if they are, the proposed estimator is asymptotically equivalent to the maximum likelihood...

Having forecast of real estate sales done correctly is very important for balancing supply and demand in the housing market. However, it is very difficult for housing companies or real estate professionals to determine how many houses they will sell next year. Although this does not mean that a...

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. A penalized least squares estimation is linked to the GLS (Aitken) estimates of the corresponding linear model with time-invariant parameters. The VC estimator is a moments...

The objective of the EU Timber Regulation (EUTR), enforced since March 2013, is for importers and exporters to commit to reducing the risk of trading timber products from illegal sources in the EU. EUROSTAT time series on monthly trade with wood products from January 1988 to August 2016 were...

Money laundering has become a global threat to the international stability and security, leading both to economic and social upheavals, and to an increase in terrorist threats. Therefore, an objective necessity arises for a more detailed study of the money laundering within the scope of its...

This article presents a new filter for state-space models based on Bellman's dynamic programming principle applied to the posterior mode. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while remaining equally inexpensive computationally....

VC implements Schlicht's method for estimating a linear regression with time-varying coefficients. The variances are estimated by a moments estimator that does not require the disturbances to be Gaussian, but if they are, it coincides with the corresponding maximum likelihood estimate in large...

The future development of population size and structure is of importance since planning in many areas of politics and business is conducted based on expectations about the future makeup of the population. Countries with both decreasing mortality and low fertility rates, which is the case for...

This contribution proposes a simulation approach for the indirect estimation of age-specific fertility rates (ASFRs) and the total fertility rate (TFR) for Germany via time series modeling of the principal components of the ASFRs. The model accounts for cross-correlation and autocorrelation...

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. A penalized least squares estimation is linked to the GLS (Aitken) estimates of the corresponding linear model with time-invariant parameters. The VC estimates are moments...

This paper is one of the limited studies to investigate rebound effects in sectoral electricity consumption and the specific case of New Zealand. New Zealand, like other OECD economies, has aimed for energy efficiency improvements and reduced electricity consumption from 9.2 MWh per capita in...

Economic sanctions are intensively used by international institutions to enforce political objectives. Since 2006 the EU has been implementing general sanctions against the whole economy of Iran, affecting their trade relations. Since 2007, and following the imposition of sanctions by the UN...

Wir stellen ein Maß für die Beziehung zwischen zwei Städten/Regionen basierend auf Suchanfragen vor, ausgehend von Merkmalen der Suchanfragen-Zeitreihen nach Zerlegung der Zeitreihe mittels STL (Komponentenzerlegung mittels lokaler linearer Kernregression). Grundlage für das Maß sind...

We propose a dynamic clustering model for studying time-varying group structures in multivariate panel data. The model is dynamic in three ways: First, the cluster means and covariance matrices are time-varying to track gradual changes in cluster characteristics over time. Second, the units of...

We consider a general class of observation-driven models with exogenous regressors for double bounded data that are based on the beta distribution. We obtain a stationary and ergodic beta observation-driven process subject to a contraction condition on the stochastic dynamic model equation. We...

I study potentials and gaps, permanent and transitory fluctuations in macroeconomic variables using the Smets and Wouter (2007) model. Model-based gaps display low frequency variations; possess more than business cycle fluctuations; have similar frequency representation as potentials, and are...

Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with q r. The present paper studies...

Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

In this paper we develop a general framework to analyze state space models with timevarying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

The phenomenon of enterprises bankruptcy is an extremely complex process of economic, legal, social and even psychological nature. In the developed countries, the first studies on forecasting bankruptcy date to the early 20th century. In Central and Eastern Europe, due to, among other factors,...

Seit Dezember 2018 liegen die Daten der VGR in Form einer Zeitreihe für die Jahre 1995 - 2018 nach den Konzepten des Europäischen Systems Volkswirtschaftlicher Gesamtrechnungen 2010 (ESVG 2010) vor. Es handelt sich dabei um revidierte Werte. Die Realwerte werden als verkettete Volumenindizes...

This paper analyzes the problem of weak instruments on identification, estimation, and inference in a simple nonparametric model of a triangular system. The paper derives a necessary and sufficient rank condition for identification, based on which weak identification is established. Then...

This paper shows how to decompose weakly stationary time series into the sum, across time scales, of uncorrelated components associated with different degrees of persistence. In particular, we provide an Extended Wold Decomposition based on an isometric scaling operator that makes averages of...

This paper examines long memory volatility in international stock markets. We show that long memory volatility is widespread in a panel dataset of eighty-two countries and that the degree of memory in the panel can be related to macroeconomic variables such as short- and long-run interest rates...

In this work we study a variant of the GARCH model when we consider the arrival of heterogeneous information in high-frequency data. This model is known as HARCH(n). We modify the HARCH(n) model when taking into consideration some market components that we consider important to the modeling...

The authors replicate and extend the Monte Carlo experiment presented in Doz et al. (2012) on alternative (time-domain based) methods for extracting dynamic factors from large datasets; they employ open source software and consider a larger number of replications and a wider set of scenarios....

In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent...

In this paper, we propose a general family of Birnbaum–Saunders autoregressive conditional duration (BS-ACD) models based on generalized Birnbaum-Saunders (GBS) distributions, denoted by GBS-ACD. We further generalize these GBS-ACD models by using a Box-Cox transformation with a shape...

We show that one should not use the one-sided Hodrick-Prescott filter (HP-1s) as the real-time version of the two-sided Hodrick-Prescott filter (HP-2s): First, in terms of the extracted cyclical component, HP-1s fails to remove low-frequency fluctuations to the same extent as HP-2s. Second,...

Purpose - The relationship between military expenditure and economic growth is complex. The purpose of this paper is to examine this relationship in India. Design/methodology/approach - The design of this study is descriptive in the theoretical part, and quantitative in the applied one. The...

The electricity price is the sensitive signal of the supply-demand balance and some other market incidents. The analysis of the price data can provide plenty of the market information. It is helpful for the participants to understand the market and improve future strategies. However, most of the...

Wind power experienced a substantial growth over the past decade especially because it has been seen as one of the best ways towards meeting climate change and emissions targets by many countries. Since wind power is not fully dispatchable, the accuracy of wind forecasts is a key element for the...

This paper examines long-range dependence in the inflation rates of the G7 countries by estimating their (fractional) order of integration d over the sample period January 1973 - March 2020. The results indicate that the series are very persistent, the estimated value of d being equal to or...