Suchergebnisse

Methods of temporal disaggregation are used to obtain high frequency time series from the same low frequency time series — so-called disaggregation—with respect to some additional consistency conditions between low and high frequency series. Conditions depend on the nature of the data — e.g., stack, flow, average and may pertain to the sum, the last value and the average of the obtained high frequency series, respectively. Temporal disaggregation methods are widely used all-over the world to disaggregate for example quarterly GDP. These methods are usually two-stage methods which consist of regression and benchmarking. In this article we propose a method which performs regression and benchmarking at the same time and allows to set a trade-off between them.

Cover -- Half Title -- Series Information -- Title Page -- Copyright Page -- Table of contents -- Figures -- Tables -- 1 Introduction -- 2 Importance of regional data for policy evaluation -- 3 A review of official statistics describing economic conditions in NUTS-2 regions in Poland -- 4 Basic properties of the model of Seemingly Unrelated Regression Equations -- 4.1 A brief look at estimation and testing within the frameworks of simple and generalised linear regression -- 4.2 Seemingly Unrelated Regression Equations as an example of generalised linear regression -- Note -- 5 NUTS-2 disaggregation of the Polish GDP: Preliminary analyses within SURE< -- sub> -- diag< -- /sub> -- -- 5.1 Basic model setting -- 5.2 Empirical results -- 5.3 Conclusions -- 6 NUTS-2 disaggregation of the Polish GDP: Including other explanatory variables -- 6.1 NUTS-2 disaggregation of the Polish GDP: analyses within a simple regression framework -- 6.1.1 Basic model setting -- 6.1.2 Empirical results -- 6.2 NUTS-2 disaggregation of the Polish GDP: analyses within the unconstrained SURE model -- 6.2.1 Basic model setting -- 6.2.2 Discussion of empirical results -- 6.2.3 Tables containing estimation results -- 6.2.4 Tables containing results obtained in case of model M0, i.e. SUREdiag -- 6.2.5 Tables containing results obtained in case of model M1, i.e. unconstrained SURE model -- 7 Concluding remarks -- Bibliography -- Index.

"This book addresses one of the most important research activities in empirical macroeconomics. It provides a course of advanced but intuitive methods and tools enabling the spatial and temporal disaggregation of basic macroeconomic variables and the assessment of the statistical uncertainty of the outcomes of disaggregation. The empirical analysis focuses mainly on GDP and its growth in the country context of Poland, however, all of the methods discussed can be easily applied to other countries. The approach used in the book, views spatial and temporal disaggregation as a special case of the estimation of missing observations (a topic on missing data analysis). The book presents an econometric course of models of Seemingly Unrelated Regression Equations (SURE). The main advantage of using the SURE specification is to tackle the presented research problem so that it allows for the heterogeneity of the parameters describing relations between macroeconomic indicators. The book contains model specification, as well as descriptions of stochastic assumptions and resulting procedures of estimation and testing. The method also addresses uncertainty in the estimates produced. All of the necessary tests and assumptions are presented in detail. The results will be designed to serve as a source of invaluable information making regional analyses more convenient and - more importantly - comparable. It will create a solid basis for making conclusions and recommendations concerning regional economic policy in Poland, particularly regarding the assessment of the economic situation. This is essential reading for academics, researchers and economists with regional analysis as their field of expertise, as well as, central bankers and policymakers."

ABSTRACTThis paper investigates the links between growth in gross domestic product (GDP) and sulfur dioxide emissions by disaggregating income growth into long-term growth (the trend of GDP over time) and short-term growth (income fluctuations around the trend). Results indicate a substantial fixed component of sulfur dioxide emissions. Once income fluctuations are controlled for, the effect of changes in the scale of the economy over time can be distinguished from the effects of the changing composition of output and the state of technological development. Results indicate that at low levels of income, the composition and technology effects are associated with an increase in emissions; for high levels of income, the composition and technology effects are associated with a leveling off of emissions.

In Mexico, the System of National Accounts is disaggregated at the State level and expressed at constant prices of the most recent base year, 2008, for the years 2003 to 2015. Another frequently used database related to the National Accounts and disaggregated by State contains a quarterly index of economic activity. Further, a yearly database is also available with State‐level disaggregation and base year 1993, but it only covers the years 1993 to 2006 and employs a different classification system from that of base year 2008. In this work, we are concerned with the problem of retropolating the database of a Mexican State called Mexico City with the maximum level of disaggregation allowed by the publicly available databases. We followed a data‐driven approach and combined the three databases to produce an estimated homogeneous quarterly database with base year 2008, covering the years 1993 to 2015 and disaggregated up to groups of sectors.

Annual estimates of the GDP of Victoria for the period 1861–1976/77 are here presented and used as a basis for an analysis of Victoria's long–run economic growth. Victoria is represented as having fallen behind the per capita GDP of Australia as a whole in the 1870s but to have out–paced the national growth rate from the early twentieth century until the late 1950s. The changing importance of natural resources and of the scope for manufacturing development are seen as the basis for an explanation of the Victorian divergence. The article carries the implication of a need for regional disaggregation in the analysis of Australian economic growth.

Business cycle indicators are important instruments for monitoring economic development. When employing indicators one usually relies on a sound statistical database. This paper deals with indicator development in a sparse data situation. Indicator building is merged with temporal disaggregation, which is often used by statistical offices. The discussed tools are applied in a case study for Abu Dhabi. Because the economy of Abu Dhabi is very dependent on oil, real income reflects the economic situation better than real gross domestic product (GDP). For this reason a measure of real gross domestic income (GDI) was chosen as reference series.

The Treasury is the New Zealand government's lead advisor on economic and financial issues. Part of this advice consists of providing the government with forecasts of economic and fiscal variables. Economic forecasts are important, not only as a basis for forecasts of tax revenue, but also in informing the government of the macroeconomic environment in which proposed fiscal policy settings will operate. The New Zealand Treasury Model (NZTM) is an important part of the economic forecasting process at the Treasury. This paper has three purposes. The first is to give readers an idea of the key features of NZTM. The second is to detail major changes to the model since the last published documentation of the model (Szeto, 2002). These model developments have enhanced NZTM to provide more detailed forecasts. Key changes include the disaggregation of deflators into the various expenditure GDP components, the introduction of consumption and capital goods imports into the model (rather than just treating them as intermediate imports) and the disaggregation of the inflation equation into tradable and non-tradable components. The final purpose of this paper is to outline briefly NZTM's role in the Treasury's forecasting process.

This paper performs a Structural VAR analysis on UK economy using quarterly non-interpolated data from 1981 to 2005 in the attempt to verify and quantify private consumption's response to different components of public expenditure (government consumption, social spending and wage component). Our findings suggest that any empirical support of competing theoretical models on the issue would probably benefit from a disaggregation of government expenditure, rather than focusing on the aggregate measure. In fact, while shocks to pure government consumption trigger a RBC-like reduction in private consumption, shocks to the non-systematic component of social spending generate positive reaction, in line with the "credit-constrained-agents" approach. The cumulative impact on GDP after three years of a government spending shock (close to a negative 1% of GDP) is twice as much the social spending shock, with opposite sign. Government wage shocks do not seem to have any significant effects on private consumption. Public expenditure composition, rather than level, seems to be actually playing the most crucial role when it comes to aggregate demand support via effects on private consumption.

This paper performs a Structural VAR analysis on UK economy using quarterly non-interpolated data from 1981 to 2005 in the attempt to verify and quantify private consumption's response to different components of public expenditure (government consumption, social spending and wage component). Our findings suggest that any empirical support of competing theoretical models on the issue would probably benefit from a disaggregation of government expenditure, rather than focusing on the aggregate measure. In fact, while shocks to pure government consumption trigger a RBC-like reduction in private consumption, shocks to the non-systematic component of social spending generate positive reaction, in line with the "credit-constrained-agents" approach. The cumulative impact on GDP after three years of a government spending shock (close to a negative 1% of GDP) is twice as much the social spending shock, with opposite sign. Government wage shocks do not seem to have any significant effects on private consumption. Public expenditure composition, rather than level, seems to be actually playing the most crucial role when it comes to aggregate demand support via effects on private consumption.