| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Data–Cleaning Augmented Kalman Filter for Robust Estimation of State Space Models |
0 |
0 |
0 |
82 |
0 |
5 |
19 |
109 |
| A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices |
0 |
0 |
0 |
59 |
0 |
3 |
11 |
64 |
| A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices |
0 |
0 |
0 |
16 |
0 |
1 |
8 |
63 |
| A Monthly Indicator of the Euro Area GDP |
0 |
0 |
0 |
91 |
1 |
13 |
40 |
353 |
| A Monthly Indicator of the Euro Area GDP |
0 |
0 |
0 |
218 |
0 |
1 |
9 |
475 |
| A data-cleaning augmented Kalman filter for robust estimation of state space models |
0 |
0 |
0 |
76 |
0 |
4 |
10 |
131 |
| A generalized exponential time series regression model for electricity prices |
0 |
0 |
1 |
135 |
0 |
3 |
11 |
178 |
| A seasonal integration analysis of the italian consumption quarterly time series |
0 |
0 |
0 |
3 |
0 |
2 |
3 |
14 |
| Band Spectral Estimation for Signal Extraction |
0 |
0 |
0 |
137 |
0 |
3 |
17 |
332 |
| Band-Pass Filtering with High-Dimensional Time Series |
0 |
0 |
0 |
5 |
0 |
1 |
14 |
33 |
| Band-Pass Filtering with High-Dimensional Time Series |
0 |
0 |
4 |
32 |
0 |
3 |
15 |
42 |
| Bayesian stochastic model specification search for seasonal and calendar effects |
0 |
0 |
1 |
37 |
1 |
5 |
13 |
121 |
| Bayesian stochastic model specification search for seasonal and calendar effects |
0 |
0 |
0 |
45 |
0 |
1 |
7 |
112 |
| Characterising the Business Cycle for Accession Countries |
0 |
0 |
0 |
312 |
0 |
7 |
17 |
717 |
| Characterising the Business Cycle for Accession Countries |
0 |
0 |
0 |
196 |
0 |
2 |
11 |
543 |
| Characterizing economic trends by Bayesian stochastic model specifi cation search |
0 |
0 |
0 |
81 |
0 |
0 |
7 |
198 |
| Characterizing economic trends by Bayesian stochastic model specification search |
0 |
0 |
0 |
55 |
0 |
2 |
9 |
167 |
| Characterizing economic trends by Bayesian stochastic model specification search |
0 |
0 |
0 |
60 |
0 |
2 |
11 |
189 |
| Characterizing the Business Cycle for Accession Countries |
0 |
0 |
0 |
175 |
1 |
5 |
14 |
557 |
| Dating the Euro Area Business Cycle |
0 |
0 |
0 |
347 |
0 |
10 |
19 |
1,153 |
| Dating the Euro Area Business Cycle |
0 |
0 |
0 |
313 |
0 |
11 |
19 |
1,092 |
| Dating the Euro Area Business Cycle |
0 |
0 |
0 |
427 |
0 |
12 |
27 |
1,370 |
| Direct and iterated multistep AR methods for difference stationary processes |
0 |
0 |
0 |
72 |
1 |
4 |
7 |
179 |
| Does the Box-Cox Transformation Help in Forecasting Macroeconomic Time Series? |
0 |
0 |
0 |
47 |
1 |
3 |
16 |
148 |
| Does the Box-Cox transformation help in forecasting macroeconomic time series? |
0 |
0 |
0 |
128 |
1 |
5 |
13 |
214 |
| Does the Box-Cox transformation help in forecasting macroeconomic time series? |
0 |
0 |
0 |
19 |
0 |
5 |
12 |
113 |
| Dynamic Factor Analysis with Nonlinear Temporal Aggregation Constraints |
0 |
0 |
0 |
291 |
0 |
4 |
19 |
574 |
| Efficient Nonparametric Estimation of Generalized Autocovariances |
0 |
0 |
1 |
22 |
0 |
1 |
10 |
42 |
| Estimating Potential Output and the Output Gap for the Euro Area: a Model-Based Production Function Approach |
0 |
0 |
1 |
950 |
1 |
4 |
12 |
2,069 |
| Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components |
0 |
0 |
1 |
180 |
3 |
6 |
18 |
438 |
| EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro |
0 |
0 |
0 |
62 |
0 |
2 |
8 |
129 |
| EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries |
0 |
0 |
0 |
68 |
0 |
6 |
22 |
170 |
| EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area |
0 |
0 |
0 |
64 |
0 |
5 |
10 |
107 |
| EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area |
0 |
0 |
0 |
32 |
0 |
4 |
10 |
136 |
| EuroMInd-D: A density estimate of monthly gross domestic product for the euro area |
0 |
0 |
0 |
20 |
0 |
3 |
17 |
114 |
| Exponential Smoothing, Long Memory and Volatility Prediction |
0 |
0 |
0 |
110 |
0 |
7 |
17 |
130 |
| Exponential Smoothing, Long Memory and Volatility Prediction |
0 |
0 |
0 |
38 |
1 |
2 |
11 |
78 |
| Exponential Smoothing, Long Memory and Volatility Prediction |
0 |
0 |
0 |
85 |
2 |
4 |
13 |
138 |
| Extracting the Cyclical Component in Hours Worked: a Bayesian Approach |
0 |
0 |
0 |
83 |
2 |
4 |
13 |
269 |
| Forecasting Volatility with Time-Varying Leverage and Volatility of Volatility Effects |
0 |
0 |
1 |
124 |
2 |
5 |
14 |
137 |
| Forecasting and Signal Extraction with Misspecified Models |
0 |
0 |
0 |
181 |
2 |
4 |
9 |
397 |
| Generalised Linear Spectral Models |
0 |
0 |
0 |
52 |
0 |
6 |
23 |
133 |
| Generalised partial autocorrelations and the mutual information between past and future |
0 |
0 |
0 |
54 |
1 |
4 |
11 |
100 |
| Generalised partial autocorrelations and the mutual information between past and future |
0 |
0 |
0 |
39 |
0 |
4 |
10 |
80 |
| Growth accounting for the euro area: a structural approach |
0 |
0 |
0 |
167 |
2 |
4 |
10 |
375 |
| Has the Volatility of U.S. Inflation Changed and How? |
0 |
0 |
0 |
166 |
1 |
1 |
10 |
346 |
| Hyper-spherical and Elliptical Stochastic Cycles |
0 |
0 |
0 |
56 |
0 |
7 |
36 |
276 |
| Leave-k-out diagnostics in state space models |
0 |
0 |
0 |
35 |
0 |
3 |
7 |
212 |
| Low-Pass Filter Design using Locally Weighted Polynomial Regression and Discrete Prolate Spheroidal Sequences |
0 |
0 |
0 |
94 |
0 |
5 |
15 |
578 |
| Maximum likelihood estimation of time series models: the Kalman filter and beyond |
0 |
0 |
0 |
185 |
0 |
4 |
12 |
307 |
| Maximum likelihood estimation of time series models: the Kalman filter and beyond |
0 |
0 |
0 |
59 |
0 |
4 |
11 |
247 |
| Measuring Core Inflation by Multivariate Structural Time Series Models |
0 |
0 |
0 |
206 |
0 |
4 |
8 |
384 |
| Modelling Cycles in Climate Series: the Fractional Sinusoidal Waveform Process |
0 |
0 |
1 |
64 |
1 |
5 |
10 |
58 |
| New proposals for the quantification of qualitative survey data |
0 |
0 |
0 |
127 |
0 |
0 |
4 |
330 |
| Nowcasting GDP and its Components in a Data-rich Environment: the Merits of the Indirect Approach |
0 |
1 |
1 |
65 |
0 |
3 |
17 |
137 |
| Nowcasting Monthly GDP with Big Data: a Model Averaging Approach |
0 |
0 |
2 |
97 |
2 |
6 |
23 |
139 |
| On the Equivalence of the Weighted Least Squares and the Generalised Least Squares Estimators, with Applications to Kernel Smoothing |
0 |
0 |
0 |
71 |
0 |
4 |
15 |
255 |
| On the Estimation of Climate Normals and Anomalies |
0 |
0 |
12 |
12 |
0 |
4 |
27 |
27 |
| On the Estimation of Nonlinearly Aggregated Mixed Models |
0 |
0 |
0 |
148 |
1 |
2 |
5 |
436 |
| On the Model Based Interpretation of Filters and the Reliability of Trend-Cycle Estimates |
0 |
0 |
0 |
87 |
0 |
5 |
12 |
242 |
| On the Model-Based Interpretation of Filters and the Reliability of Trend-Cycle Estimates |
0 |
1 |
1 |
297 |
0 |
3 |
11 |
624 |
| On the Selection of Common Factors for Macroeconomic Forecasting |
0 |
0 |
0 |
36 |
0 |
0 |
6 |
80 |
| On the Selection of Common Factors for Macroeconomic Forecasting |
0 |
0 |
0 |
76 |
0 |
3 |
4 |
125 |
| On the Selection of Common Factors for Macroeconomic Forecasting |
0 |
0 |
0 |
39 |
0 |
2 |
12 |
67 |
| On the Spectral Properties of Matrices Associated with Trend Filters |
0 |
0 |
0 |
32 |
0 |
6 |
19 |
182 |
| Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach |
0 |
0 |
1 |
173 |
2 |
3 |
8 |
112 |
| Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach |
0 |
0 |
0 |
39 |
1 |
6 |
11 |
190 |
| Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach |
0 |
0 |
1 |
43 |
0 |
2 |
32 |
173 |
| Outlier detection in structural time series models: The indicator saturation approach |
0 |
0 |
1 |
57 |
2 |
7 |
18 |
135 |
| Patterns of industrial specialisation in post-Unification Italy |
0 |
0 |
0 |
67 |
1 |
2 |
8 |
107 |
| Patterns of industrial specialisation in post-unification Italy |
0 |
0 |
0 |
2 |
1 |
2 |
7 |
26 |
| Peaks, Gaps, and Time Reversibility of Economic Time Series |
0 |
0 |
0 |
59 |
0 |
1 |
12 |
77 |
| Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models |
0 |
0 |
0 |
78 |
1 |
4 |
11 |
102 |
| Real Time Estimation in Local Polynomial Regression, with Application to Trend-Cycle Analysis |
0 |
0 |
0 |
93 |
0 |
4 |
19 |
338 |
| Seasonal Changes in Central England Temperatures |
0 |
0 |
0 |
31 |
0 |
2 |
8 |
103 |
| Seasonal Changes in Central England Temperatures |
0 |
0 |
0 |
31 |
0 |
2 |
8 |
60 |
| Seasonal Specific Structural Time Series Models |
0 |
0 |
0 |
257 |
0 |
2 |
2 |
435 |
| Seasonality in High Frequency Time Series |
0 |
0 |
1 |
75 |
0 |
7 |
31 |
123 |
| Seasonality, Forecast Extensions and Business Cycle Uncertainty |
0 |
0 |
0 |
160 |
0 |
8 |
20 |
418 |
| Some Reflections on Trend-Cycle Decompositions with Correlated Components |
0 |
0 |
0 |
162 |
1 |
5 |
13 |
344 |
| Some Reflections on Trend-Cycle Decompositions with Correlated Components |
0 |
0 |
0 |
309 |
0 |
3 |
17 |
586 |
| Spikes and Memory in (Nord Pool) Electricity Price Spot Prices |
0 |
0 |
0 |
42 |
0 |
3 |
21 |
85 |
| Spikes and memory in (Nord Pool) electricity price spot prices |
0 |
0 |
0 |
4 |
0 |
4 |
11 |
53 |
| Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search |
0 |
0 |
0 |
13 |
0 |
2 |
10 |
77 |
| Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search |
0 |
0 |
0 |
89 |
0 |
1 |
8 |
181 |
| Structural Time Series Modelling of Capacity Utilisation |
0 |
0 |
0 |
8 |
0 |
3 |
6 |
42 |
| Structural Time Series Models for Business Cycle Analysis |
0 |
0 |
0 |
66 |
0 |
5 |
15 |
184 |
| Structural Time Series Models for Business Cycle Analysis |
0 |
0 |
0 |
681 |
1 |
4 |
12 |
1,466 |
| Structural properties of the new quarterly series on consumption |
0 |
0 |
0 |
1 |
0 |
1 |
2 |
15 |
| Survey Data as Coicident or Leading Indicators |
0 |
0 |
0 |
72 |
1 |
5 |
16 |
218 |
| Survey Data as Coincident or Leading Indicators |
0 |
0 |
0 |
38 |
0 |
1 |
10 |
176 |
| Temporal Disaggregation by State Space Methods: Dynamic Regression Methods Revisited |
0 |
0 |
3 |
506 |
1 |
13 |
26 |
1,191 |
| The Effects of Unification: Markets, Policy and Cyclical Convergence in Italy, 1861-1913 |
0 |
0 |
0 |
109 |
0 |
7 |
19 |
351 |
| The Exponential Model for the Spectrum of a Time Series: Extensions and Applications |
0 |
0 |
0 |
32 |
1 |
3 |
5 |
69 |
| The Exponential Model for the Spectrum of a Time Series: Extensions and Applications |
0 |
0 |
0 |
42 |
0 |
4 |
9 |
74 |
| The Exponential Model for the Spectrum of a Time Series: Extensions and Applications |
0 |
0 |
0 |
97 |
0 |
2 |
11 |
120 |
| The Generalised Autocovariance Function |
0 |
0 |
0 |
70 |
1 |
5 |
10 |
145 |
| The Generalised Autocovariance Function |
0 |
0 |
0 |
28 |
2 |
4 |
10 |
109 |
| The Multistep Beveridge-Nelson Decomposition |
0 |
0 |
0 |
244 |
0 |
3 |
9 |
590 |
| The Multistep Beveridge-Nelson Decomposition |
0 |
0 |
0 |
75 |
0 |
4 |
10 |
193 |
| The Multistep Beveridge-Nelson Decomposition |
0 |
0 |
0 |
14 |
2 |
5 |
8 |
78 |
| The Variance Profile |
0 |
0 |
0 |
58 |
0 |
0 |
8 |
209 |
| The comovements of construction in Italy's regions, 1861-1913 |
0 |
0 |
0 |
62 |
0 |
4 |
24 |
209 |
| Transformations and Seasonal Adjustment: Analytic Solutions and Case Studies |
0 |
0 |
0 |
49 |
1 |
3 |
9 |
174 |
| Trend Estimation |
0 |
0 |
1 |
161 |
0 |
1 |
9 |
366 |
| Ups and (Draw)Downs |
1 |
2 |
4 |
21 |
1 |
8 |
23 |
46 |
| Total Working Papers |
1 |
4 |
39 |
11,960 |
47 |
418 |
1,406 |
29,085 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| 2nd Special Issue on Statistical Signal Extraction and Filtering |
0 |
0 |
0 |
23 |
0 |
1 |
1 |
63 |
| A Beveridge-Nelson smoother |
0 |
0 |
0 |
122 |
0 |
2 |
10 |
252 |
| A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices |
0 |
0 |
0 |
11 |
0 |
4 |
12 |
44 |
| A Systemic Approach to Estimating the Output Gap for the Italian Economy |
0 |
0 |
2 |
29 |
1 |
4 |
17 |
93 |
| A class of periodic trend models for seasonal time series |
0 |
0 |
1 |
12 |
0 |
3 |
8 |
34 |
| A data-cleaning augmented Kalman filter for robust estimation of state space models |
0 |
0 |
1 |
9 |
1 |
3 |
15 |
62 |
| Another Look at Dependence: The Most Predictable Aspects of Time Series |
0 |
0 |
0 |
0 |
1 |
4 |
13 |
13 |
| Band spectral estimation for signal extraction |
0 |
0 |
0 |
44 |
0 |
2 |
16 |
176 |
| Business Cycles in the New EU Member Countries and their Conformity with the Euro Area |
0 |
0 |
0 |
80 |
0 |
1 |
13 |
229 |
| Characterising economic trends by Bayesian stochastic model specification search |
0 |
0 |
0 |
9 |
0 |
4 |
8 |
87 |
| Characterizing Asymmetries in Business Cycles Using Smooth-Transition Structural Time-Series Models |
0 |
0 |
0 |
91 |
0 |
0 |
4 |
240 |
| Comparing seasonal components for structural time series models |
0 |
1 |
3 |
210 |
1 |
3 |
17 |
628 |
| Component-wise Representations of Long-memory Models and Volatility Prediction |
0 |
0 |
1 |
17 |
1 |
3 |
8 |
59 |
| Convergence in Italian regional per-capita GDP |
0 |
0 |
0 |
158 |
0 |
2 |
10 |
551 |
| Dating Business Cycles: A Methodological Contribution with an Application to the Euro Area |
0 |
1 |
1 |
196 |
0 |
5 |
18 |
582 |
| Direct and iterated multistep AR methods for difference stationary processes |
0 |
0 |
1 |
15 |
0 |
6 |
14 |
98 |
| Direct and iterated multistep AR methods for difference stationary processes |
0 |
0 |
0 |
5 |
1 |
1 |
4 |
37 |
| Discussion of The class of CUB models: statistical foundations, inferential issues and empirical evidence |
0 |
0 |
0 |
7 |
0 |
2 |
4 |
24 |
| Does the Box–Cox transformation help in forecasting macroeconomic time series? |
0 |
0 |
1 |
53 |
2 |
5 |
19 |
268 |
| Dynamic factor analysis with non‐linear temporal aggregation constraints |
0 |
0 |
0 |
88 |
2 |
6 |
18 |
280 |
| EUROMIND: a monthly indicator of the euro area economic conditions |
0 |
0 |
0 |
0 |
0 |
5 |
18 |
242 |
| Editorial |
0 |
0 |
0 |
1 |
1 |
2 |
5 |
11 |
| Efficient nonparametric estimation of generalised autocovariances |
1 |
1 |
1 |
1 |
1 |
3 |
7 |
9 |
| Estimating potential output and the output gap for the euro area: a model-based production function approach |
0 |
0 |
0 |
211 |
0 |
3 |
14 |
543 |
| Estimation of Common Factors under Cross‐Sectional and Temporal Aggregation Constraints |
0 |
0 |
0 |
6 |
0 |
2 |
9 |
40 |
| EuroMInd-C: A disaggregate monthly indicator of economic activity for the Euro area and member countries |
0 |
0 |
0 |
11 |
0 |
0 |
10 |
77 |
| Euromind‐ D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area |
0 |
0 |
0 |
4 |
1 |
4 |
14 |
68 |
| Extracting the Cyclical Component in Hours Worked |
0 |
0 |
0 |
27 |
0 |
3 |
7 |
121 |
| Forecasting and signal extraction with misspecified models |
0 |
0 |
0 |
55 |
3 |
5 |
11 |
204 |
| Forecasting the US unemployment rate |
0 |
0 |
4 |
168 |
1 |
4 |
14 |
363 |
| Forecasting volatility with time-varying leverage and volatility of volatility effects |
0 |
0 |
0 |
10 |
0 |
4 |
14 |
45 |
| Growth accounting for the euro area |
0 |
0 |
1 |
18 |
0 |
2 |
12 |
89 |
| Has the Volatility of U.S. Inflation Changed and How? |
0 |
0 |
2 |
79 |
0 |
1 |
15 |
229 |
| Hyper‐spherical and elliptical stochastic cycles |
0 |
0 |
0 |
14 |
0 |
2 |
4 |
64 |
| Introduction |
0 |
0 |
0 |
11 |
0 |
2 |
6 |
86 |
| LEAVE‐K‐OUT DIAGNOSTICS IN STATE‐SPACE MODELS |
0 |
0 |
0 |
74 |
1 |
3 |
9 |
259 |
| Missing data in time series: A note on the equivalence of the dummy variable and the skipping approaches |
0 |
0 |
0 |
45 |
1 |
4 |
9 |
112 |
| Modelling cycles in climate series: The fractional sinusoidal waveform process |
0 |
0 |
0 |
9 |
1 |
5 |
14 |
33 |
| Multivariate temporal disaggregation with cross-sectional constraints |
0 |
0 |
1 |
22 |
1 |
5 |
11 |
110 |
| New algorithms for dating the business cycle |
0 |
0 |
0 |
66 |
0 |
2 |
6 |
135 |
| New proposals for the quantification of qualitative survey data |
0 |
0 |
0 |
34 |
0 |
2 |
11 |
100 |
| Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach |
0 |
0 |
1 |
20 |
0 |
3 |
14 |
67 |
| Nowcasting monthly GDP with big data: A model averaging approach |
0 |
0 |
3 |
27 |
1 |
5 |
21 |
93 |
| ON THE SPECTRAL PROPERTIES OF MATRICES ASSOCIATED WITH TREND FILTERS |
0 |
0 |
0 |
11 |
0 |
3 |
11 |
60 |
| On the Model-Based Interpretation of Filters and the Reliability of Trend-Cycle Estimates |
0 |
0 |
0 |
55 |
0 |
9 |
14 |
160 |
| On the equivalence of the weighted least squares and the generalised least squares estimators, with applications to kernel smoothing |
0 |
0 |
0 |
10 |
0 |
6 |
14 |
66 |
| Outlier detection in structural time series models: The indicator saturation approach |
0 |
0 |
3 |
21 |
3 |
10 |
32 |
132 |
| Patterns of industrial specialisation in post-Unification Italy |
0 |
0 |
1 |
14 |
1 |
2 |
8 |
70 |
| Peaks, gaps, and time‐reversibility of economic time series |
0 |
0 |
0 |
5 |
0 |
3 |
8 |
27 |
| Persistence of Shocks on Seasonal Processes |
0 |
0 |
0 |
55 |
0 |
4 |
9 |
215 |
| Predictability, real time estimation, and the formulation of unobserved components models |
0 |
0 |
0 |
6 |
0 |
0 |
4 |
22 |
| SEASONALITY, FORECAST EXTENSIONS AND BUSINESS CYCLE UNCERTAINTY |
0 |
0 |
0 |
29 |
0 |
4 |
8 |
124 |
| Seasonal Specific Structural Time Series |
0 |
0 |
0 |
84 |
0 |
4 |
10 |
250 |
| Seasonal changes in central England temperatures |
0 |
0 |
0 |
11 |
0 |
3 |
9 |
62 |
| Seasonality in High Frequency Time Series |
1 |
2 |
7 |
20 |
2 |
8 |
26 |
58 |
| Short-Run Dynamics in Cointegrated Systems |
0 |
0 |
0 |
0 |
0 |
2 |
12 |
416 |
| Signal extraction and filtering by linear semiparametric methods |
0 |
0 |
0 |
46 |
1 |
5 |
13 |
142 |
| Spurious periodic autoregressions |
0 |
0 |
0 |
0 |
0 |
2 |
6 |
324 |
| State space modeling of Gegenbauer processes with long memory |
0 |
0 |
0 |
22 |
1 |
1 |
7 |
75 |
| Stochastic trends and seasonality in economic time series: new evidence from Bayesian stochastic model specification search |
0 |
0 |
0 |
12 |
1 |
2 |
7 |
81 |
| Survey data as coincident or leading indicators |
0 |
0 |
0 |
58 |
0 |
1 |
14 |
190 |
| Temporal disaggregation by state space methods: Dynamic regression methods revisited |
0 |
0 |
0 |
160 |
0 |
3 |
19 |
550 |
| The Multistep Beveridge--Nelson Decomposition |
0 |
0 |
0 |
9 |
1 |
3 |
7 |
47 |
| The Variance Profile |
0 |
0 |
0 |
19 |
0 |
0 |
2 |
104 |
| The effects of unification: markets, policy, and cyclical convergence in Italy, 1861–1913 |
0 |
0 |
0 |
55 |
1 |
2 |
9 |
295 |
| The generalised autocovariance function |
0 |
0 |
0 |
22 |
2 |
5 |
13 |
120 |
| Transformations and seasonal adjustment |
0 |
0 |
0 |
33 |
0 |
2 |
10 |
111 |
| Trend-Cycle Decompositions with Correlated Components |
0 |
0 |
2 |
76 |
0 |
3 |
11 |
203 |
| Trends in atmospheric ethane |
0 |
0 |
0 |
9 |
0 |
1 |
15 |
37 |
| Unobserved components models with correlated disturbances |
0 |
0 |
0 |
3 |
0 |
3 |
4 |
14 |
| Total Journal Articles |
2 |
5 |
37 |
2,937 |
35 |
223 |
786 |
10,875 |