Analysis of seasonal and other short-term variations with applications to Finnish economic time series

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dc.contributor Suomen Pankki
dc.contributor.author Kukkonen, Pertti
dc.date.accessioned 2017-08-15T09:44:15Z
dc.date.available 2017-08-15T09:44:15Z
dc.date.issued 1968
dc.identifier.issn 0357-4776
dc.identifier.uri https://helda.helsinki.fi/bof/handle/123456789/14872
dc.description.tableofcontents 1. INTRODUCTION 9 2. THE METHOD OF ITERATED MOVING AVERAGES 2.1. General Remarks 12 2.2. Weighted Moving Averages 13 2.3. Computational Steps 15 3. THE METHOD OF ITERATED MOVING AVERAGES AS A METHOD OF ESTIMATION 3.1. Constant Seasonal Patterns 18 3.1.1. The Method of Moving Averages in Operator Notation 19 3.1.2. Some Concepts of Spectral Analysis 21 3.1.3. The Efficiency of Iteration 22 3.1.4. HANNAN's Estimator for Constant Seasonal Patterns 24 3.2. Changing Seasonal Patterns 25 3.2.1. The Frequency Response Function of the Filters C 26 3.2.2. Expectation of the Estimate of the Seasonal Component 31 3.2.3. Iteration and the Slutzky-Yule Effect 36 3.2.4. On the Treatment of the First and Last Observations in a Time Series 42 3.3. Examples of the Application of the Method of Iterated Moving Averages 45 3.4. Alternative Methods 48 4. REGRESSION ANALYSIS AS A METHOD OF ESTIMATING SHORT-TERM VARIATIONS 4.1. Effect of the Residual Component on the Forecast Error in the Case of Optimal Linear Filters 51 4.2. On Defining the Seasonal and Calendar Variations in Regression Analysis 53 4.3. Various Types of Models Employed in the Regression Analysis of Seasonal and Calendar Variations 59 4.4. The Least Squares of Differences Method 61 4.4.1. The Criterion Suggested by RUIST 62 4.4.2. The Least-squares Criterion for Differences and the Classical Linear Regression Model 63 4.4.3. Restrictions on the Parameters 67 4.4.4. The Method of Restricted Least Squares 69 4.4.5. A Computational Procedure for the Method of Restricted Least Squares 70 4.5. Elimination of Seasonal and Calendar Variations from the Time-series Data for Econometric Models through the Regression Method 75 4.5.1. LOVELL's Theorem 76 4.5.2. The Effect of Linear Restrictions 79 4.5.3. The Trend-cycle Component, Calendar Variations and Short-term Changes in the Seasonal Pattern 82 4.6. Applications of the Regression Method 84 4.6.1. Specification of the Trend-cycle Component in Applications of the Least Squares of Differences Method 85 4.6.2. Abrupt Changes in the Seasonal Pattern 97 4.6.3. Calendar Variations100 4.6.4. The Special Seasonal Variations due to Unseasonal Weather Conditions103 4.6.5. The Impact of the Choice of a Seasonal Adjustment Method on the Estimation of a Demand for Labour Model109 4.6.6. A Summary of the Application of the Least Squares of Differences Method114 REFERENCES 115 LIST OF SYMBOLS 117 APPENDIX 1. The Bank of Finland Method of Iterated Moving Averages for the Analysis of Seasonal Variations 119 APPENDIX 2. The Weights of Alternative Smoothing Formulae in the Method of Iterated Moving Averages 123 APPENDIX 3. Finnish Economic Time Series Data Used in Applications 128
dc.format.extent 135
dc.language.iso ENG
dc.rights https://helda.helsinki.fi/bof/copyright
dc.subject.other time-series
dc.title Analysis of seasonal and other short-term variations with applications to Finnish economic time series
dc.type Book
dc.identifier.urn URN:NBN:fi:bof-201708151535
dc.series.name Suomen Pankin taloustieteellisen tutkimuslaitoksen julkaisuja. B
dc.series.number 28
dc.series.sortingnumber 0028
dc.date.publication 1.4.1968
dc.subject.yso aikasarjat
dc.subject.yso ekonometria
dc.subject.yso ekonometriset mallit
dc.subject.yso ennusteet
dc.subject.yso suhdannevaihtelut
dc.subject.yso aikasarja-analyysi

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