| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| "Borrowing money costs money": Yes, but why not tell how much? |
0 |
0 |
0 |
30 |
0 |
0 |
2 |
58 |
| A Dynamic Utility Maximization Model for Product Category Consumption |
0 |
0 |
0 |
209 |
0 |
0 |
2 |
799 |
| A Hierarchical Bayes Error Correction Model to Explain Dynamic Effects of Price Changes |
0 |
0 |
0 |
107 |
0 |
1 |
2 |
383 |
| A Joint Framework for Category Purchase and Consumption Behavior |
0 |
0 |
0 |
130 |
0 |
0 |
0 |
522 |
| A Manager's Perspective on Combining Expert and Model-based Forecasts |
0 |
0 |
0 |
76 |
0 |
0 |
0 |
99 |
| A Multi-Level Panel Smooth Transition Autoregression for US Sectoral Production |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
460 |
| A Multivariate STAR Analysis of the Relationship Between Money and Output |
0 |
0 |
0 |
252 |
0 |
1 |
1 |
667 |
| A Multivariate STAR Analysis of the Relationship Between Money and Output |
0 |
0 |
0 |
357 |
0 |
2 |
3 |
842 |
| A New Multivariate Product Growth Model |
0 |
0 |
0 |
123 |
0 |
0 |
1 |
427 |
| A Novel Approach to Measuring Consumer Confidence |
0 |
0 |
0 |
33 |
2 |
4 |
5 |
68 |
| A generalized dynamic conditional correlation model for many asset returns |
0 |
0 |
1 |
67 |
0 |
0 |
3 |
170 |
| A hierarchical Bayes error correction model to explain dynamic effects |
0 |
0 |
0 |
16 |
0 |
0 |
2 |
85 |
| A model for quarterly unemployment in Canada |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
40 |
| A multi-level panel smooth transition autoregression for US sectoral production |
0 |
0 |
0 |
38 |
0 |
0 |
3 |
123 |
| A multivariate STAR analysis of the relationship between money and output |
0 |
0 |
0 |
127 |
0 |
0 |
1 |
317 |
| A nonlinear long memory model for US unemployment |
0 |
0 |
1 |
45 |
0 |
0 |
2 |
99 |
| A seasonal periodic long memory model for monthly river flows |
0 |
0 |
0 |
24 |
0 |
0 |
1 |
120 |
| A sequential approach to testing seasonal unit roots in high frequency data |
0 |
0 |
0 |
33 |
0 |
0 |
2 |
106 |
| A simple test for GARCH against a stochastic volatility |
0 |
0 |
0 |
35 |
0 |
0 |
1 |
101 |
| A simple test for PPP among traded goods |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
76 |
| AN EMPIRICAL TEST FOR PARITIES BETWEEN METAL PRICES AT THE IME |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
392 |
| Advertising effects on awareness, consideration and brand choice using tracking data |
0 |
0 |
0 |
221 |
0 |
0 |
0 |
837 |
| Aggregate statistics on trafficker-destination relations in the Atlantic slave trade |
0 |
0 |
0 |
20 |
0 |
0 |
1 |
28 |
| Aggregate statistics on trafficker-destination relations in the Atlantic slave trade |
0 |
0 |
0 |
39 |
0 |
2 |
4 |
41 |
| An Empirical Study of Cash Payments |
0 |
0 |
0 |
149 |
0 |
0 |
0 |
386 |
| An Equilibrium-Correction Model for Dynamic Network Data |
0 |
0 |
0 |
858 |
0 |
0 |
2 |
3,002 |
| An empirical analysis of euro cash payments |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
43 |
| An introduction to time-varying lag autoregression |
0 |
0 |
1 |
86 |
0 |
1 |
4 |
80 |
| Analysis of the Maritime Inspection Regimes - Are ships over-inspected? |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
155 |
| Analyzing Fixed-Event Forecast Revisions |
0 |
0 |
0 |
25 |
0 |
1 |
2 |
87 |
| Analyzing Fixed-event Forecast Revisions |
0 |
0 |
0 |
71 |
0 |
1 |
1 |
120 |
| Analyzing Fixed-event Forecast Revisions |
0 |
0 |
0 |
60 |
0 |
2 |
2 |
85 |
| Analyzing Fixed-event Forecast Revisions |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
64 |
| Analyzing Fixed-event Forecast Revisions |
0 |
0 |
0 |
89 |
0 |
1 |
1 |
195 |
| Analyzing Fixed-event Forecast Revisions |
0 |
0 |
0 |
9 |
0 |
2 |
2 |
86 |
| Analyzing preferences ranking when there are too many alternatives |
0 |
0 |
1 |
35 |
0 |
0 |
2 |
78 |
| Approximating the DGP of China's Quarterly GDP |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
170 |
| Are Chinese Individuals prone to Money Illusion? |
0 |
0 |
0 |
23 |
0 |
0 |
0 |
91 |
| Are Forecast Updates Progressive? |
0 |
0 |
0 |
27 |
0 |
0 |
0 |
122 |
| Are Forecast Updates Progressive? |
0 |
0 |
0 |
24 |
0 |
0 |
0 |
134 |
| Are Forecast Updates Progressive? |
0 |
0 |
0 |
33 |
0 |
0 |
0 |
88 |
| Are Forecast Updates Progressive? |
0 |
0 |
0 |
28 |
1 |
3 |
4 |
88 |
| Are Forecast Updates Progressive? |
0 |
0 |
0 |
22 |
0 |
0 |
0 |
96 |
| Are Forecast Updates Progressive? |
0 |
0 |
0 |
28 |
0 |
1 |
2 |
135 |
| Are Forecast Updates Progressive? |
0 |
0 |
0 |
39 |
0 |
0 |
2 |
148 |
| Are we in a bubble? A simple time-series-based diagnostic |
0 |
0 |
0 |
174 |
0 |
0 |
1 |
108 |
| Asymmetric Time Aggregation and its Potential Benefits for Forecasting Annual Data |
0 |
0 |
0 |
46 |
0 |
0 |
1 |
139 |
| Asymmetric and Common Absorption of Shocks in Nonlinear Autoregressive Models |
0 |
0 |
0 |
99 |
0 |
1 |
3 |
294 |
| Asymmetric and Common Abssorbtion of Shocks in Nonlinear Autoregressive Models |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
254 |
| Asymmetric and common absorption of shocks in nonlinear autoregressive models |
0 |
0 |
0 |
26 |
0 |
0 |
5 |
102 |
| Bayesian Analysis of Seasonal Unit Roots and Seasonal Mean Shifts |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
60 |
| Bayesian Model Averaging in the Presence of Structural Breaks |
0 |
0 |
0 |
35 |
0 |
0 |
1 |
130 |
| Benchmarking judgmentally adjusted forecasts |
0 |
0 |
0 |
27 |
1 |
3 |
3 |
38 |
| Big Data Analysis of Volatility Spillovers of Brands across Social Media and Stock Markets |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
51 |
| Broker Positions in Task-Specific Knowledge Networks |
0 |
0 |
0 |
99 |
0 |
1 |
1 |
597 |
| Buying High Tech Products |
0 |
0 |
0 |
122 |
0 |
0 |
0 |
469 |
| Censored latent effects autoregression, with an application to US unemployment |
0 |
0 |
0 |
18 |
0 |
1 |
1 |
58 |
| Censored regression analysis in large samples with many zero observations |
0 |
0 |
0 |
45 |
0 |
0 |
0 |
131 |
| Changing Perceptions and Changing Behavior in Customer Relationships |
0 |
0 |
0 |
442 |
0 |
0 |
1 |
1,383 |
| Cointegration in a historical perspective |
0 |
0 |
0 |
110 |
0 |
0 |
0 |
141 |
| Cointegration in a periodic vector autoregression |
0 |
0 |
0 |
22 |
0 |
0 |
0 |
68 |
| Combining Non-Replicable Forecasts |
0 |
0 |
0 |
38 |
1 |
1 |
1 |
101 |
| Combining Non-Replicable Forecasts |
0 |
0 |
0 |
21 |
0 |
0 |
1 |
68 |
| Common large innovations across nonlinear time series |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
47 |
| Competence and confidence effects in experts' forecast adjustments |
0 |
0 |
0 |
27 |
0 |
0 |
3 |
55 |
| Comprehensive review of the maritime safety regimes |
0 |
0 |
0 |
31 |
0 |
0 |
1 |
90 |
| Confidence Intervals for Cronbach's Coefficient Alpha Values |
0 |
1 |
3 |
964 |
1 |
4 |
13 |
4,009 |
| Confidence intervals for maximal reliability of probability judgments |
0 |
0 |
0 |
9 |
0 |
0 |
0 |
65 |
| Consensus forecasters: How good are they individually and why? |
0 |
0 |
0 |
46 |
0 |
0 |
5 |
67 |
| Consideration sets, intentions and the inclusion of "Don't know" in a two-stage model for voter choice |
0 |
0 |
0 |
9 |
0 |
0 |
0 |
90 |
| Constructing seasonally adjusted data with time-varying confidence intervals |
0 |
0 |
0 |
24 |
0 |
0 |
0 |
102 |
| Convergence and Persistence of Left-Right Political Orientations in The Netherlands 1978-1995 |
0 |
0 |
0 |
5 |
0 |
0 |
2 |
57 |
| Correcting for Survey Effects in Pre-election Polls |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
131 |
| Cycles in basic innovations |
0 |
0 |
1 |
22 |
0 |
0 |
2 |
82 |
| Decomposing bias in expert forecast |
0 |
0 |
0 |
62 |
1 |
1 |
2 |
61 |
| Deriving Target Selection Rules from Endogenously Selected Samples |
0 |
0 |
0 |
124 |
0 |
3 |
4 |
589 |
| Deriving dynamic marketing effectiveness from econometric time series models |
0 |
0 |
1 |
143 |
0 |
1 |
3 |
362 |
| Determining the Order of Differencing in Seasonal Time Series Processes |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
262 |
| Did the incidence of high precipitation levels increase? Statistical evidence for the Netherlands |
0 |
0 |
0 |
4 |
0 |
1 |
1 |
51 |
| Diffusion of Original and Counterfeit Products in a Developing Country |
0 |
0 |
0 |
32 |
0 |
0 |
5 |
121 |
| Diffusion of counterfeit medical products in a developing country: Empirical evidence for Suriname |
0 |
0 |
0 |
17 |
0 |
1 |
1 |
73 |
| Do African economies grow similarly? |
0 |
0 |
2 |
66 |
0 |
0 |
2 |
69 |
| Do Charities Get More when They Ask More Often? Evidence from a Unique Field Experiment |
0 |
0 |
0 |
77 |
0 |
0 |
3 |
165 |
| Do Commercial Real Estate Prices Have Predictive Content for GDP |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
165 |
| Do Experts incorporate Statistical Model Forecasts and should they? |
0 |
0 |
0 |
28 |
1 |
1 |
2 |
103 |
| Do Experts' SKU Forecasts improve after Feedback? |
0 |
0 |
0 |
30 |
0 |
0 |
1 |
82 |
| Do We Often Find ARCH Because Of Neglected Outliers? |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
45 |
| Do experts incorporate statistical model forecasts and should they? |
0 |
0 |
0 |
18 |
0 |
0 |
2 |
90 |
| Do experts' SKU forecasts improve after feedback? |
0 |
0 |
0 |
15 |
1 |
2 |
2 |
50 |
| Do loss profiles on the mortgage market resonate with changes in macro economic prospects, business cycle movements or policy measures? |
0 |
0 |
0 |
21 |
0 |
0 |
2 |
77 |
| Do the US and Canada have a common nonlinear cycle in unemployment? |
0 |
0 |
0 |
6 |
0 |
1 |
1 |
57 |
| Do we make better forecasts these days? A survey amongst academics |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
32 |
| Do we need all Euro denominations? |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
173 |
| Does Africa grow slower than Asia and Latin America? |
0 |
0 |
0 |
12 |
0 |
0 |
2 |
55 |
| Does Disagreement Amongst Forecasters have Predictive Value? |
0 |
0 |
0 |
40 |
0 |
1 |
1 |
64 |
| Does Disagreement amongst Forecasters have Predictive Value? |
0 |
0 |
0 |
51 |
1 |
1 |
3 |
77 |
| Does Irritation Induced by Charitable Direct Mailings Reduce Donations? |
0 |
0 |
0 |
40 |
0 |
1 |
1 |
174 |
| Does More Expert Adjustment Associate with Less Accurate Professional Forecasts? |
0 |
0 |
0 |
17 |
0 |
0 |
1 |
37 |
| Does a financial crisis make consumers increasingly prudent? |
0 |
0 |
0 |
32 |
1 |
1 |
1 |
62 |
| Does experts' adjustment to model-based forecasts contribute to forecast quality? |
0 |
0 |
0 |
7 |
0 |
0 |
1 |
34 |
| Does news on real Chinese GDP growth impact stock markets? |
0 |
0 |
0 |
42 |
0 |
0 |
1 |
106 |
| Does ratification matter and do major conventions improve safety and decrease pollution in shipping? |
0 |
0 |
0 |
22 |
0 |
0 |
1 |
86 |
| Does rounding matter for payment efficiency? |
0 |
0 |
1 |
2 |
0 |
0 |
2 |
48 |
| Does the FOMC Have Expertise, and Can It Forecast? |
0 |
0 |
1 |
64 |
0 |
0 |
1 |
112 |
| Does the ROMC have expertise, and can it forecast? |
0 |
0 |
1 |
10 |
1 |
1 |
4 |
138 |
| Dynamic Effects of Trust and Cognitive Social Structures on Information Transfer Relationships |
0 |
0 |
0 |
151 |
0 |
1 |
2 |
584 |
| Dynamic and Competitive Effects of Direct Mailings |
0 |
0 |
0 |
59 |
0 |
0 |
1 |
194 |
| Dynamics of expert adjustment to model-based forecast |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
72 |
| Ecological panel inference in repeated cross sections |
0 |
0 |
0 |
5 |
1 |
1 |
2 |
28 |
| Econometric Analysis of the Market Share Attraction Model |
0 |
1 |
6 |
1,330 |
0 |
1 |
15 |
3,801 |
| Effect and Improvement Areas for Port State Control Inspections to Decrease the Probability of Casualty |
0 |
0 |
0 |
23 |
0 |
1 |
2 |
109 |
| Effectiveness of Brokering within Account Management Organizations |
0 |
0 |
0 |
64 |
0 |
0 |
2 |
259 |
| Emigration, wage differentials and brain drain: The case of Suriname |
0 |
0 |
0 |
86 |
0 |
0 |
2 |
200 |
| Estimated Parameters Do Not Get the "Wrong Sign" Due To Collinearity Across Included Variables |
0 |
0 |
0 |
86 |
1 |
1 |
1 |
337 |
| Estimates of quarterly GDP growth using MIDAS regressions |
0 |
0 |
2 |
51 |
0 |
0 |
5 |
151 |
| Estimating Loss Functions of Experts |
0 |
1 |
2 |
35 |
0 |
1 |
2 |
76 |
| Estimating Loss Functions of Experts |
0 |
0 |
1 |
13 |
0 |
0 |
1 |
43 |
| Estimating duration intervals |
0 |
0 |
0 |
58 |
0 |
0 |
1 |
166 |
| Estimating persistence for irregularly spaced historical data |
0 |
0 |
0 |
73 |
1 |
1 |
2 |
48 |
| Estimating the market share attraction model using support vector regressions |
0 |
0 |
0 |
57 |
1 |
1 |
2 |
262 |
| Evaluating Combined Non-Replicable Forecast |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
82 |
| Evaluating Combined Non-Replicable Forecasts |
0 |
0 |
1 |
8 |
0 |
1 |
3 |
51 |
| Evaluating Combined Non-Replicable Forecasts |
0 |
0 |
0 |
19 |
0 |
0 |
0 |
81 |
| Evaluating Direct Marketing Campaigns: recent findings and future research topics |
0 |
0 |
0 |
622 |
0 |
0 |
1 |
1,824 |
| Evaluating Individual and Mean Non-Replicable Forecasts |
0 |
0 |
0 |
11 |
0 |
0 |
0 |
79 |
| Evaluating Individual and Mean Non-Replicable Forecasts |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
144 |
| Evaluating Individual and Mean Non-Replicable Forecasts |
0 |
0 |
0 |
22 |
0 |
1 |
1 |
87 |
| Evaluating Macroeconomic Forecast: A Review of Some Recent Developments |
0 |
0 |
0 |
92 |
0 |
2 |
2 |
223 |
| Evaluating Macroeconomic Forecasts: A Concise Review of Some Recent Developments |
0 |
0 |
0 |
97 |
0 |
1 |
2 |
151 |
| Evaluating Macroeconomic Forecasts: A Concise Review of Some Recent Developments |
0 |
0 |
0 |
166 |
0 |
3 |
6 |
220 |
| Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments |
0 |
0 |
0 |
94 |
0 |
0 |
1 |
175 |
| Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments |
0 |
0 |
0 |
94 |
0 |
0 |
0 |
288 |
| Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments |
0 |
0 |
0 |
60 |
0 |
1 |
1 |
161 |
| Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments |
0 |
0 |
0 |
127 |
0 |
0 |
1 |
172 |
| Evaluating Macroeconomic Forecasts:A Concise Review of Some Recent Developments |
0 |
0 |
0 |
72 |
1 |
1 |
1 |
191 |
| Evaluating heterogeneous forecasts for vintages of macroeconomic variables |
0 |
0 |
0 |
57 |
0 |
0 |
0 |
36 |
| Evaluating real-time forecasts in real-time |
0 |
0 |
0 |
21 |
0 |
0 |
3 |
93 |
| Evaluating the Rationality of Managers' Sales Forecasts |
0 |
0 |
0 |
50 |
0 |
0 |
0 |
60 |
| Evaluation of survey effects in pre-election polls |
0 |
0 |
1 |
46 |
0 |
0 |
2 |
358 |
| Experimental investigation of consumer price evaluations |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
42 |
| Expert opinion versus expertise in forecasting |
0 |
0 |
0 |
91 |
0 |
0 |
2 |
471 |
| Experts adjusting model-based forecasts and the law of small numbers |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
29 |
| Experts' Stated Behavior |
0 |
0 |
0 |
23 |
0 |
0 |
0 |
91 |
| Experts' adjustment to model-based forecasts: Does the forecast horizon matter? |
0 |
0 |
0 |
8 |
1 |
1 |
1 |
47 |
| Exploiting Spillovers to forecast Crashes |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
54 |
| Financial innumeracy |
0 |
0 |
0 |
26 |
0 |
0 |
1 |
142 |
| Forecasting 1 to h steps ahead using partial least squares |
0 |
0 |
0 |
38 |
0 |
0 |
0 |
117 |
| Forecasting Annual Inflation in Suriname |
0 |
0 |
0 |
41 |
1 |
1 |
3 |
85 |
| Forecasting Earnings Forecasts |
0 |
0 |
0 |
21 |
0 |
0 |
1 |
50 |
| Forecasting Market Shares from Models for Sales |
0 |
0 |
1 |
599 |
0 |
1 |
2 |
1,605 |
| Forecasting Sales |
0 |
0 |
1 |
121 |
0 |
0 |
4 |
294 |
| Forecasting aggregates using panels of nonlinear time series |
0 |
0 |
0 |
18 |
0 |
0 |
0 |
82 |
| Forecasting economic and financial time-series with non-linear models |
0 |
0 |
0 |
876 |
1 |
2 |
2 |
1,662 |
| Forecasting high-frequency electricity demand with a diffusion index model |
0 |
0 |
0 |
22 |
0 |
0 |
3 |
89 |
| Forecasting in marketing |
0 |
0 |
1 |
40 |
0 |
0 |
1 |
87 |
| Forecasting own brand sales: Does incorporating competition help? |
0 |
0 |
1 |
30 |
0 |
1 |
4 |
41 |
| Forecasting social conflicts in Africa using an Epidemic Type Aftershock Sequence model |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
23 |
| Forecasting the Levels of Vector Autoregressive Log-Transformed Time Series |
0 |
0 |
0 |
17 |
0 |
1 |
1 |
70 |
| Forecasting volatility with switching persistence GARCH models |
0 |
0 |
0 |
22 |
0 |
0 |
1 |
71 |
| Forecasting with periodic autoregressive time series models |
0 |
0 |
0 |
70 |
0 |
2 |
3 |
148 |
| Forecasting: theory and practice |
0 |
0 |
5 |
90 |
3 |
4 |
21 |
116 |
| Formalizing judgemental adjustment of model-based forecasts |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
66 |
| Franses |
0 |
0 |
0 |
149 |
1 |
2 |
4 |
1,617 |
| From first submission to citation: an empirical analysis |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
29 |
| Gaussian Copula Regression in the Presence of Thresholds |
0 |
0 |
3 |
31 |
3 |
3 |
11 |
60 |
| Heterogeneity in Manufacturing Growth Risk |
0 |
0 |
0 |
10 |
0 |
1 |
4 |
36 |
| How Accurate are Government Forecast of Economic Fundamentals? |
0 |
0 |
0 |
57 |
0 |
1 |
3 |
148 |
| How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan |
0 |
0 |
1 |
28 |
0 |
1 |
2 |
226 |
| How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
138 |
| How Accurate are Government Forecasts of Economic Fundamentals? The Case of Taiwan |
0 |
0 |
0 |
51 |
0 |
0 |
0 |
225 |
| How Informative are the Unpredictable Components of Earnings Forecasts? |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
36 |
| How Large is Average Economic Growth? Evidence from a Robust Method |
0 |
0 |
0 |
65 |
1 |
1 |
1 |
314 |
| How do we pay with euro notes? Empirical evidence from Monopoly experiments |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
69 |
| How to deal with intercept and trend in pratical cointegration analysis? |
0 |
0 |
0 |
138 |
0 |
0 |
0 |
314 |
| How to gain brain for Suriname |
0 |
0 |
0 |
13 |
0 |
1 |
1 |
39 |
| IMA(1,1) as a new benchmark for forecast evaluation |
0 |
0 |
0 |
26 |
0 |
0 |
1 |
62 |
| Impulse Response Functions for Periodic Integration |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
596 |
| Impulse-response analysis of the market share attraction model |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
125 |
| Income, Cultural Norms and Purchases of Counterfeits |
0 |
0 |
0 |
19 |
0 |
1 |
1 |
66 |
| Incorporating Responsiveness to Marketing Efforts When Modeling Brand Choice |
0 |
0 |
0 |
149 |
0 |
0 |
0 |
526 |
| Incorporating responsiveness to marketing efforts in brand choice modelling |
0 |
0 |
0 |
22 |
1 |
1 |
2 |
84 |
| Indirect Network Effects in New Product Growth |
0 |
0 |
0 |
115 |
0 |
0 |
3 |
449 |
| Inequality amongst the wealthiest and its link with economic growth |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
25 |
| Inequality amongst the wealthiest and its link with economic growth |
0 |
0 |
0 |
45 |
0 |
0 |
0 |
85 |
| Inferring transition probabilities from repeated cross sections: a cross-level inference approach to US presidential voting |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
56 |
| Inflation rates; long-memoray, level shifts, or both? |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
25 |
| Inflation, Forecast Intervals and Long Memory Regression Models |
0 |
0 |
2 |
617 |
0 |
0 |
3 |
2,103 |
| Interaction Between Shelf Layout and Marketing Effectiveness and Its Impact On Optimizing Shelf Arrangements |
0 |
0 |
1 |
185 |
0 |
0 |
4 |
830 |
| Interlocking Boards and Firm Performance: Evidence from a New Panel Database |
0 |
0 |
2 |
158 |
0 |
2 |
6 |
732 |
| Interpreting Financial Market Crashes as Earthquakes: A New early Warning System for Medium Term Crashes |
0 |
0 |
1 |
98 |
0 |
1 |
2 |
170 |
| Intertemporal Similarity of Economic Time Series |
0 |
0 |
3 |
85 |
0 |
0 |
5 |
117 |
| Irritation Due to Direct Mailings from Charities |
0 |
0 |
0 |
56 |
0 |
0 |
0 |
197 |
| Jury report on the KVS award for the best Doctoral Thesis in Economics of the academic years 2006-2007 and 2007-2008 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
13 |
| Long Memory and Level Shifts: Re-Analyzing Inflation Rates |
0 |
0 |
0 |
181 |
0 |
0 |
0 |
783 |
| Long memory and level shifts: re-analysing inflation rates |
0 |
0 |
0 |
17 |
0 |
2 |
2 |
80 |
| Long-term forecast for the Dutch economy |
0 |
0 |
1 |
9 |
0 |
0 |
1 |
39 |
| Low-fat, light, and reduced in calories |
0 |
0 |
0 |
33 |
0 |
0 |
2 |
64 |
| Managing Sales Forecasters |
0 |
0 |
0 |
72 |
0 |
1 |
1 |
61 |
| Measuring the effect of perceived corruption on detention and incident risk – an empirical analysis |
0 |
0 |
0 |
2 |
0 |
0 |
5 |
23 |
| Measuring weekly consumer confidence |
0 |
0 |
0 |
57 |
0 |
0 |
1 |
104 |
| Microeconomic determinants of skilled migration: The case of Suriname |
0 |
0 |
0 |
64 |
2 |
4 |
4 |
122 |
| Model selection for forecast combination |
0 |
0 |
0 |
95 |
0 |
0 |
0 |
143 |
| Model-based forecast adjustment; with an illustration to inflation |
0 |
0 |
0 |
34 |
0 |
0 |
1 |
53 |
| Modeling Consideration Sets and Brand Choice Using Artificial Neural Networks |
0 |
0 |
0 |
308 |
0 |
0 |
2 |
928 |
| Modeling Dynamic Effects of the Marketing Mix on Market Shares |
0 |
0 |
0 |
384 |
0 |
0 |
2 |
1,142 |
| Modeling Generational Transitions from Aggregate Data |
0 |
0 |
0 |
51 |
0 |
1 |
1 |
227 |
| Modeling Potentially Time-Varying Effects of Promotions on Sales |
0 |
0 |
1 |
289 |
0 |
1 |
3 |
865 |
| Modeling Seasonality in New Product Diffusion |
0 |
0 |
0 |
79 |
0 |
0 |
2 |
185 |
| Modeling Unobserved Consideration Sets for Household Panel Data |
0 |
0 |
0 |
203 |
0 |
0 |
0 |
1,036 |
| Modeling and forecasting outliers and level shifts in absolute returns |
0 |
0 |
0 |
16 |
0 |
0 |
0 |
53 |
| Modeling asymmetric volatility in weekly Dutch temperature data |
0 |
0 |
0 |
26 |
0 |
1 |
1 |
73 |
| Modeling charity donations: target selection, response time and gift size |
0 |
0 |
1 |
133 |
0 |
0 |
8 |
370 |
| Modeling dynamic effects of promotion on interpurchase times |
0 |
0 |
0 |
24 |
0 |
0 |
2 |
103 |
| Modeling purchases as repeated events |
0 |
0 |
0 |
27 |
0 |
1 |
3 |
103 |
| Modeling regional house prices |
0 |
0 |
0 |
159 |
0 |
1 |
1 |
290 |
| Modeling students' evealuation scores; comparing economics schools in Maastricht and Rotterdam |
0 |
0 |
0 |
2 |
1 |
2 |
2 |
46 |
| Modeling the Effectiveness of Hourly Direct-Response Radio Commercials |
0 |
0 |
0 |
27 |
0 |
0 |
0 |
168 |
| Modeling the diffusion of scientific publications |
0 |
0 |
1 |
6 |
0 |
1 |
2 |
66 |
| Modeling the effectiveness of hourly direct-response radio commercials |
0 |
0 |
0 |
41 |
0 |
0 |
0 |
231 |
| Modelling Multiple Regimes in the Business Cycle |
0 |
0 |
1 |
58 |
0 |
1 |
4 |
168 |
| Modelling asymmetric persistence over the business cycle |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
53 |
| Modelling health care expenditures; overview of the literature and evidence from a panel time series model |
0 |
0 |
0 |
324 |
0 |
0 |
2 |
793 |
| Monitoring structural change in variance |
0 |
0 |
0 |
23 |
0 |
0 |
1 |
74 |
| Monitoring time-varying parameters in an autoregression |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
38 |
| Nonlinear Error-Correction Models for Interest Rates in The Netherlands |
0 |
0 |
0 |
70 |
0 |
0 |
4 |
179 |
| Nonlinearities and outliers: robust specification of STAR models |
0 |
0 |
0 |
42 |
0 |
0 |
3 |
146 |
| On Forecasting Cointegrated Seasonal Time Series |
0 |
0 |
1 |
422 |
0 |
1 |
2 |
1,153 |
| On Phillips-Perron Type Tests for Seasonal Unit Roots |
0 |
0 |
0 |
135 |
0 |
0 |
2 |
1,016 |
| On SETAR non- linearity and forecasting |
0 |
0 |
0 |
54 |
0 |
0 |
1 |
126 |
| On combining revealed and stated preferences to forecast customer behaviour: three case studies |
0 |
0 |
0 |
29 |
0 |
1 |
2 |
94 |
| On data transformations and evidence of nonlinearity |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
28 |
| On forecasting cointegrated seasonal time series |
0 |
0 |
0 |
13 |
1 |
2 |
4 |
50 |
| On modeling panels of time series |
0 |
0 |
0 |
11 |
0 |
0 |
0 |
28 |
| On the Bass diffusion theory, empirical models and out-of-sample forecasting |
0 |
0 |
0 |
324 |
0 |
0 |
1 |
1,104 |
| On the diffusion of scientific publications; the case of Econometrica 1987 |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
36 |
| On the econometrics of the Koyck model |
0 |
1 |
8 |
444 |
2 |
6 |
36 |
4,023 |
| On the number of categories in an ordered regression model |
0 |
0 |
1 |
24 |
0 |
0 |
1 |
75 |
| On the optimality of expert-adjusted forecasts |
0 |
0 |
0 |
25 |
0 |
0 |
0 |
55 |
| On the optimality of expert-adjusted forecasts |
0 |
0 |
0 |
30 |
0 |
0 |
1 |
116 |
| On the role of seasonal intercepts in seasonal cointegration |
0 |
0 |
0 |
43 |
0 |
0 |
1 |
218 |
| On the role of seasonal intercepts in seasonal cointegration |
0 |
0 |
0 |
16 |
0 |
1 |
3 |
59 |
| Ordered logit analysis for selectively sampled data |
0 |
0 |
0 |
33 |
0 |
0 |
1 |
129 |
| Outlier Robust Analysis of Market Share and Distribution Relations for Weekly Scanning Data |
0 |
0 |
0 |
4 |
2 |
3 |
5 |
46 |
| Outlier detection in the GARCH (1,1) model |
0 |
0 |
0 |
34 |
1 |
2 |
2 |
109 |
| Outlier robust cointegration analysis |
0 |
0 |
0 |
240 |
0 |
0 |
2 |
566 |
| Outliers and judgemental adjustment of time series forecasts |
0 |
0 |
0 |
43 |
0 |
1 |
3 |
89 |
| Panel design effects on response rates and response quality |
0 |
0 |
0 |
11 |
0 |
1 |
1 |
85 |
| Performance of Seasonal Adjustment Procedures: Simulation and Empirical Results |
0 |
0 |
0 |
29 |
0 |
1 |
3 |
145 |
| Prediction beyond the survey sample: correcting for survey effects on consumer decisions |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
83 |
| Professional Forecasters and January |
0 |
0 |
1 |
97 |
1 |
1 |
14 |
418 |
| Purchasing complex services on the Internet; An analysis of mortgage loan acquisitions |
0 |
0 |
0 |
82 |
0 |
0 |
1 |
396 |
| Random-Coefficient periodic autoregression |
0 |
0 |
0 |
28 |
0 |
0 |
3 |
118 |
| Ranking Models in Conjoint Analysis |
0 |
0 |
0 |
58 |
1 |
2 |
4 |
128 |
| Real GDP growth in Africa, 1963-2016 |
0 |
0 |
2 |
56 |
0 |
0 |
3 |
110 |
| Real time estimates of GDP growth |
0 |
0 |
0 |
47 |
0 |
0 |
3 |
102 |
| Real time estimates of GDP growth, based on two-regime models |
0 |
0 |
0 |
23 |
0 |
0 |
0 |
56 |
| Recovering historical inflation data from postal stamps prices |
0 |
0 |
0 |
61 |
0 |
0 |
1 |
65 |
| Reference-based transitions in short-run price elasticity |
0 |
1 |
1 |
68 |
0 |
3 |
3 |
370 |
| Retrieving unobserved consideration sets from household panel data |
0 |
0 |
0 |
62 |
1 |
2 |
3 |
157 |
| Return migration of high skilled workers |
0 |
0 |
0 |
45 |
0 |
0 |
1 |
80 |
| Risk Perception and Decision-Making by the Corporate Elite: Empirical Evidence for Netherlands-based Companies |
0 |
0 |
0 |
16 |
0 |
0 |
4 |
109 |
| Risk attitudes in company boardrooms in a developing country |
0 |
0 |
0 |
12 |
1 |
1 |
1 |
50 |
| Risk attitudes in the board room and company performance: Evidence for an emerging economy |
0 |
0 |
0 |
18 |
0 |
0 |
1 |
56 |
| Robust inference on average economic growth |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
29 |
| SEASONALITY, NONSTATIONARITY AND THE FORECASTING OF MONTHLY TIME SERIES |
0 |
0 |
4 |
9 |
0 |
1 |
10 |
37 |
| SEASONALITY, OUTLIERS AND LINEARITY |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
10 |
| SETS, Arbitrage Activity, and Stock Price Dynamics |
0 |
0 |
0 |
310 |
0 |
0 |
2 |
1,383 |
| Sales Models For Many Items Using Attribute Data |
0 |
0 |
0 |
201 |
0 |
0 |
0 |
771 |
| Seasonal adjustment and the business cycle in unemployment |
0 |
0 |
0 |
14 |
0 |
1 |
2 |
60 |
| Seasonal smooth transition autoregression |
0 |
0 |
0 |
39 |
0 |
0 |
0 |
123 |
| Seasonality in revisions of macroeconomic data |
0 |
0 |
0 |
26 |
0 |
1 |
1 |
56 |
| Seasonality on non-linear price effects in scanner-data based market-response models |
0 |
0 |
0 |
19 |
0 |
0 |
0 |
85 |
| Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy |
0 |
0 |
0 |
14 |
0 |
0 |
1 |
70 |
| Semi-Parametric Modelling of Correlation Dynamics |
0 |
0 |
0 |
58 |
0 |
0 |
0 |
139 |
| Short Patches of Outliers, ARCH and Volatility Modeling |
0 |
0 |
0 |
281 |
1 |
1 |
1 |
1,016 |
| Size and value effects in Suriname |
0 |
0 |
0 |
9 |
0 |
0 |
0 |
63 |
| Smooth Transition Autoregressive Models - A Survey of Recent Developments |
0 |
0 |
2 |
1,810 |
0 |
1 |
10 |
3,412 |
| Smooth transition autoregressive models - A survey of recent developments |
0 |
1 |
4 |
460 |
0 |
2 |
13 |
882 |
| Specification Testing in Hawkes Models |
0 |
0 |
0 |
29 |
0 |
0 |
0 |
63 |
| Spurious Principal Components |
0 |
0 |
1 |
54 |
0 |
0 |
1 |
49 |
| Stability through cycles |
0 |
0 |
0 |
35 |
0 |
0 |
1 |
63 |
| Statistical Institutes and Economic Prosperity |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
85 |
| Stochastic levels and duration dependence in US unemployment |
0 |
0 |
1 |
39 |
1 |
1 |
2 |
34 |
| Structural breaks and long memory in US inflation rates: do they matter for forecasting? |
0 |
0 |
0 |
26 |
0 |
0 |
3 |
89 |
| TESTING FOR SEASONAL UNIT ROOTS IN MONTHLY DATA |
1 |
1 |
4 |
73 |
1 |
1 |
6 |
127 |
| TESTING FOR WHITE NOISE IN TIME SERIES MODELS |
0 |
0 |
0 |
8 |
1 |
2 |
4 |
45 |
| THE GOMPERTZ CURVE: ESTIMATION AND SELECTION |
0 |
0 |
0 |
3 |
0 |
0 |
2 |
14 |
| Temporal aggregation in a periodically integrated autoregressive process |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
24 |
| Temporal aggregation in a periodically integrated autoregressive process |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
6 |
| Testing Changing Harmonic Regressors |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
66 |
| Testing Earning Management |
0 |
0 |
0 |
95 |
0 |
0 |
0 |
268 |
| Testing Nested and Non-Nested Periodically Integrated Autoregressive Models |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
25 |
| Testing Nested and Non-Nested Periodically Integrated Autoregressive Models |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
| Testing Nested and Non-Nested Periodically Integrated Autoregressive Models |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
268 |
| Testing changes in consumer confidence indicators |
0 |
0 |
0 |
25 |
0 |
0 |
2 |
86 |
| Testing common deterministic seasonality |
0 |
0 |
0 |
7 |
1 |
1 |
1 |
38 |
| Testing for ARCH in the Presence of Additive Outliers |
0 |
0 |
0 |
26 |
0 |
0 |
2 |
141 |
| Testing for Common Deterministic Trend Slopes |
0 |
0 |
0 |
43 |
1 |
1 |
4 |
249 |
| Testing for Smooth Transition Nonlinearity in the Presence of Outliers |
0 |
0 |
0 |
47 |
0 |
1 |
2 |
143 |
| Testing for common deterministic trend slopes |
0 |
0 |
0 |
14 |
0 |
0 |
1 |
189 |
| Testing for converging deterministic seasonal variation in European industrial production |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
32 |
| Testing for harmonic regressors |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
23 |
| Testing for seasonal unit roots in monthly panels of time series |
0 |
0 |
0 |
77 |
0 |
2 |
3 |
160 |
| The Cash Use of the Malaysian Ringgit |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
2 |
| The Davies Problem: A New Test for Random Slope in the Hierarchical Linear Model |
0 |
0 |
0 |
36 |
0 |
2 |
3 |
146 |
| The Econometrics Of The Bass Diffusion Model |
0 |
0 |
1 |
990 |
0 |
0 |
4 |
3,130 |
| The Effect of Relational Constructs on Relationship Performance |
0 |
0 |
0 |
563 |
2 |
2 |
3 |
1,584 |
| The Global View on Port State Control |
0 |
0 |
1 |
36 |
0 |
0 |
1 |
118 |
| The Impact of Mobile Telephone Use on Economic Development of Households in Uganda |
0 |
0 |
0 |
59 |
1 |
4 |
11 |
192 |
| The Late 1970's Bubble in Dutch Collectible Postage Stamps |
0 |
0 |
1 |
16 |
1 |
2 |
5 |
102 |
| The Launch Timing of New and Dominant Multigeneration Technologies |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
96 |
| The Overall View of the Effect of Inspections and Evaluation of the Target Factor to target substandard vessels |
0 |
0 |
0 |
11 |
0 |
0 |
0 |
49 |
| The Stock Exchange of Suriname: Returns, Volatility, Correlations and Weak-form Efficiency |
0 |
0 |
1 |
65 |
0 |
1 |
3 |
197 |
| The Triggers, Timing and Speed of New Product Price Landings |
0 |
0 |
0 |
62 |
0 |
0 |
1 |
181 |
| The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production |
0 |
0 |
0 |
25 |
0 |
0 |
0 |
85 |
| The hemline and the economy: is there any match? |
4 |
13 |
78 |
659 |
18 |
39 |
218 |
1,990 |
| The impact of brand and category characteristics on consumer stock-out reactions |
0 |
0 |
0 |
296 |
0 |
1 |
4 |
971 |
| The life cycle of social media |
0 |
0 |
2 |
128 |
1 |
2 |
5 |
158 |
| This time it is different! Or not? |
0 |
0 |
0 |
43 |
0 |
2 |
2 |
77 |
| Time-Series Models in Marketing |
0 |
0 |
0 |
578 |
0 |
0 |
1 |
1,376 |
| Timing of Vote Decision in First and Second Order Dutch Elections 1978-1995: Evidence from Artificial Neural Networks |
0 |
0 |
0 |
19 |
0 |
0 |
0 |
85 |
| To Aggregate or Not to Aggregate: Should decisions and models have the same frequency? |
0 |
0 |
0 |
46 |
0 |
0 |
1 |
59 |
| Using Selective Sampling for Binary Choice Models to Reduce Survey Costs |
0 |
0 |
0 |
194 |
0 |
0 |
0 |
838 |
| Visualizing attitudes towards service levels |
0 |
0 |
0 |
6 |
0 |
1 |
1 |
49 |
| Volatility Patterns and Spillovers in Bund Futures |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
512 |
| Volatility Spillovers Across User-Generated Content and Stock Market Performance |
0 |
0 |
0 |
42 |
0 |
0 |
2 |
64 |
| What Makes a Great Journal Great in the Sciences? Which Came First, the Chicken or the Egg? |
0 |
0 |
0 |
25 |
0 |
1 |
5 |
116 |
| What drives the Quotes of Earnings Forecasters? |
0 |
0 |
0 |
19 |
0 |
0 |
1 |
76 |
| What drives the relevance and quality of experts' adjustment to model-based forecasts? |
0 |
0 |
0 |
4 |
0 |
5 |
7 |
43 |
| When Should Nintendo Launch its Wii? Insights From a Bivariate Successive Generation Model |
0 |
0 |
0 |
89 |
0 |
0 |
1 |
352 |
| Which Brands gain Share from which Brands? Inference from Store-Level Scanner Data |
0 |
0 |
0 |
108 |
0 |
0 |
1 |
354 |
| Which brands gain share from which brands? Inference from store-level scanner data |
0 |
0 |
0 |
62 |
0 |
0 |
0 |
159 |
| Why Consumers Buy Lottery Tickets When the Sun Goes Down on Them. The Depleting Nature of Weather-Induced Bad Moods |
0 |
0 |
1 |
70 |
0 |
1 |
4 |
373 |
| Yet another look at MIDAS regression |
0 |
0 |
1 |
271 |
1 |
3 |
5 |
105 |
| Total Working Papers |
5 |
20 |
170 |
29,413 |
75 |
231 |
898 |
95,242 |
| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets |
0 |
0 |
0 |
94 |
0 |
2 |
5 |
244 |
| A Simple Test for GARCH Against a Stochastic Volatility Model |
0 |
0 |
0 |
55 |
0 |
0 |
0 |
134 |
| A UNIFYING VIEW ON MULTI‐STEP FORECASTING USING AN AUTOREGRESSION |
0 |
0 |
0 |
18 |
0 |
1 |
1 |
73 |
| A co-integration approach to forecasting freight rates in the dry bulk shipping sector |
0 |
0 |
1 |
74 |
1 |
1 |
3 |
263 |
| A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables |
0 |
1 |
10 |
1,045 |
0 |
1 |
17 |
2,878 |
| A global view on port state control: econometric analysis of the differences across port state control regimes |
0 |
0 |
2 |
17 |
0 |
0 |
4 |
44 |
| A method to select between periodic cointegration and seasonal cointegration |
0 |
0 |
0 |
31 |
0 |
0 |
1 |
87 |
| A model selection procedure for time series with seasonality |
0 |
0 |
0 |
17 |
0 |
0 |
2 |
54 |
| A model selection strategy for time series with increasing seasonal variation |
0 |
0 |
0 |
15 |
0 |
0 |
2 |
83 |
| A model selection test for an AR (1) versus an MA (1) model |
0 |
0 |
0 |
22 |
0 |
0 |
0 |
128 |
| A multi-level panel STAR model for US manufacturing sectors |
0 |
0 |
4 |
379 |
0 |
0 |
10 |
1,024 |
| A multivariate approach to modeling univariate seasonal time series |
0 |
0 |
0 |
69 |
0 |
0 |
2 |
164 |
| A nonlinear long memory model, with an application to US unemployment |
0 |
0 |
0 |
134 |
0 |
1 |
2 |
345 |
| A note on monitoring time-varying parameters in an autoregression |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
17 |
| A note on the Mean Absolute Scaled Error |
0 |
0 |
2 |
23 |
0 |
2 |
8 |
141 |
| A novel approach to measuring consumer confidence |
0 |
0 |
0 |
7 |
0 |
0 |
0 |
29 |
| A periodic cointegration model of quarterly consumption |
0 |
0 |
0 |
2 |
0 |
1 |
3 |
10 |
| A periodic long-memory model for quarterly UK inflation |
0 |
0 |
0 |
42 |
0 |
1 |
1 |
148 |
| A sequential approach to testing seasonal unit roots in high frequency data |
0 |
0 |
0 |
72 |
1 |
2 |
3 |
226 |
| A simple test for PPP among traded goods |
0 |
0 |
0 |
93 |
1 |
2 |
3 |
293 |
| A simple test for a bubble based on growth and acceleration |
0 |
0 |
3 |
27 |
1 |
1 |
5 |
64 |
| Absorption of shocks in nonlinear autoregressive models |
0 |
0 |
0 |
48 |
0 |
1 |
5 |
159 |
| Additive outliers, GARCH and forecasting volatility |
0 |
1 |
3 |
215 |
0 |
1 |
4 |
427 |
| Adoption of Falsified Medical Products in a Low-Income Country: Empirical Evidence for Suriname |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
50 |
| Adstock revisited |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
| An Empirical Study of Cash Payments |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
67 |
| An empirical analysis of euro cash payments |
0 |
0 |
0 |
24 |
0 |
0 |
0 |
91 |
| An empirical test for parities between metal prices at the LME |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
25 |
| An unbiased variance estimator for overlapping returns |
0 |
0 |
2 |
270 |
0 |
0 |
2 |
773 |
| Analyzing a panel of seasonal time series: Does seasonality in industrial production converge across Europe? |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
68 |
| Analyzing fixed-event forecast revisions |
0 |
0 |
0 |
14 |
0 |
0 |
0 |
91 |
| Approximating the DGP of China's quarterly GDP |
0 |
0 |
0 |
32 |
0 |
1 |
3 |
227 |
| Are African business cycles synchronized? Evidence from spatio-temporal modeling |
1 |
1 |
6 |
12 |
1 |
3 |
19 |
30 |
| Are forecast updates progressive? |
0 |
0 |
0 |
6 |
0 |
1 |
1 |
45 |
| Are individuals in China prone to money illusion? |
0 |
0 |
0 |
11 |
0 |
6 |
12 |
97 |
| Are living standards converging? |
0 |
0 |
0 |
84 |
0 |
0 |
4 |
283 |
| Asymmetric time aggregation and its potential benefits for forecasting annual data |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
32 |
| Asymptotically perfect and relative convergence of productivity |
0 |
0 |
0 |
285 |
0 |
1 |
4 |
847 |
| Autoregressive conditional durations: An application to the Surinamese dollar versus the US dollar exchange rate |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
5 |
| Averaging Model Forecasts and Expert Forecasts: Why Does It Work? |
0 |
0 |
0 |
3 |
0 |
2 |
2 |
14 |
| Bayesian analysis of seasonal unit roots and seasonal mean shifts |
0 |
0 |
0 |
25 |
1 |
2 |
4 |
112 |
| Benchmarking Judgmentally Adjusted Forecasts |
0 |
0 |
0 |
2 |
0 |
0 |
1 |
11 |
| Can Managers Judgmental Forecasts Be Made Scientifically? |
0 |
0 |
1 |
35 |
0 |
0 |
3 |
110 |
| Cash Use of the Taiwan Dollar: Is It Efficient? † |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
33 |
| Cointegration Analysis of Seasonal Time Series |
0 |
0 |
1 |
12 |
0 |
0 |
1 |
42 |
| Cointegration in a historical perspective |
0 |
0 |
1 |
29 |
0 |
2 |
5 |
135 |
| Combining expert‐adjusted forecasts |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
12 |
| Common large innovations across nonlinear time series |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
34 |
| Common socio-economic cycle periods |
0 |
0 |
0 |
24 |
0 |
0 |
2 |
96 |
| Comprehensive Review of the Maritime Safety Regimes: Present Status and Recommendations for Improvements |
1 |
1 |
1 |
7 |
1 |
1 |
4 |
40 |
| Conditions that make ventures thrive: from individual entrepreneur to innovation impact |
0 |
0 |
0 |
0 |
1 |
2 |
5 |
8 |
| Consideration sets, intentions and the inclusion of "don't know" in a two-stage model for voter choice |
0 |
0 |
0 |
8 |
0 |
1 |
2 |
99 |
| Constant vs. Changing Seasonality |
0 |
0 |
0 |
41 |
0 |
0 |
2 |
127 |
| Constructing Seasonally Adjusted Data with Time‐varying Confidence Intervals |
1 |
1 |
1 |
1 |
1 |
2 |
2 |
13 |
| Consumer price evaluations through choice experiments |
0 |
0 |
0 |
10 |
0 |
0 |
2 |
49 |
| Correcting for survey effects in pre‐election polls |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
24 |
| Correcting the January optimism effect |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
12 |
| Critical values for unit root tests in seasonal time series |
0 |
0 |
0 |
182 |
1 |
1 |
3 |
439 |
| Data revisions and periodic properties of macroeconomic data |
0 |
0 |
0 |
7 |
0 |
1 |
3 |
52 |
| Deriving target selection rules from endogenously selected samples |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
11 |
| Deriving target selection rules from endogenously selected samples |
0 |
0 |
0 |
56 |
0 |
2 |
2 |
252 |
| Detecting seasonal unit roots in a structural time series model |
0 |
0 |
0 |
35 |
0 |
0 |
0 |
115 |
| Determining the order of differencing in seasonal time series processes |
0 |
0 |
0 |
19 |
0 |
0 |
1 |
440 |
| Do Experts’ SKU Forecasts Improve after Feedback? |
0 |
0 |
0 |
3 |
0 |
0 |
3 |
33 |
| Do We Think We Make Better Forecasts Than in the Past? A Survey of Academics |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
8 |
| Do charities get more when they ask more often? Evidence from a unique field experiment |
0 |
0 |
0 |
13 |
0 |
1 |
1 |
87 |
| Do commercial real estate prices have predictive content for GDP? |
0 |
0 |
0 |
5 |
0 |
1 |
1 |
47 |
| Do experts' adjustments on model-based SKU-level forecasts improve forecast quality? |
1 |
2 |
2 |
40 |
1 |
5 |
7 |
204 |
| Do seasonal unit roots matter for forecasting monthly industrial production? |
0 |
0 |
0 |
37 |
0 |
1 |
1 |
206 |
| Do statistical forecasting models for SKU-level data benefit from including past expert knowledge? |
0 |
0 |
0 |
37 |
0 |
1 |
3 |
225 |
| Does Africa grow slower than Asia, Latin America and the Middle East? Evidence from a new data-based classification method |
0 |
0 |
0 |
166 |
4 |
6 |
9 |
392 |
| Does Disagreement Amongst Forecasters Have Predictive Value? |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
19 |
| Does More Expert Adjustment Associate with Less Accurate Professional Forecasts? |
0 |
0 |
1 |
3 |
0 |
0 |
1 |
29 |
| Does Seasonality Influence the Dating of Business Cycle Turning Points? |
0 |
0 |
0 |
35 |
0 |
2 |
3 |
140 |
| Does irritation induced by charitable direct mailings reduce donations? |
0 |
0 |
0 |
8 |
0 |
3 |
5 |
60 |
| Does news on real Chinese GDP growth impact stock markets? |
0 |
0 |
0 |
39 |
0 |
0 |
0 |
111 |
| Does ratification matter and do major conventions improve safety and decrease pollution in shipping? |
0 |
2 |
2 |
16 |
0 |
3 |
3 |
88 |
| Dynamic Specification and Cointegration |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
329 |
| EVALUATING MACROECONOMIC FORECASTS: A CONCISE REVIEW OF SOME RECENT DEVELOPMENTS |
0 |
0 |
0 |
17 |
0 |
1 |
4 |
91 |
| Econometric analysis on the effect of port state control inspections on the probability of casualty: Can targeting of substandard ships for inspections be improved? |
0 |
0 |
1 |
15 |
0 |
3 |
5 |
98 |
| Econometric analysis to differentiate effects of various ship safety inspections |
0 |
0 |
0 |
17 |
0 |
2 |
4 |
124 |
| Editorial |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
19 |
| Editorial |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
21 |
| Editorial Statistics |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
13 |
| Editorial introduction |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
3 |
| Editorial statistics |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
23 |
| Editorial statistics |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
29 |
| Emigration, wage differentials and brain drain: the case of Suriname |
0 |
0 |
3 |
31 |
1 |
3 |
13 |
119 |
| Empirical causality between bigger banknotes and inflation |
0 |
1 |
3 |
65 |
0 |
2 |
5 |
166 |
| Error-correction modelling in discrete and continuous time |
0 |
0 |
0 |
28 |
0 |
0 |
1 |
97 |
| Estimating Transition Probabilities from a Time Series of Independent Cross Sections |
0 |
0 |
0 |
22 |
0 |
0 |
0 |
70 |
| Estimating loss functions of experts |
0 |
0 |
0 |
4 |
0 |
1 |
1 |
16 |
| Estimating persistence for irregularly spaced historical data |
0 |
0 |
0 |
2 |
0 |
0 |
2 |
5 |
| Estimating the Market Share Attraction Model using Support Vector Regressions |
0 |
0 |
0 |
25 |
0 |
1 |
1 |
210 |
| Estimating the stock of postwar Dutch postal stamps |
0 |
0 |
0 |
9 |
0 |
1 |
1 |
82 |
| Estimating volatility on overlapping returns when returns are autocorrelated |
0 |
0 |
0 |
225 |
0 |
0 |
3 |
613 |
| Evaluating CPB’s Forecasts |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
62 |
| Evaluating Individual and Mean Non-Replicable Forecasts |
0 |
0 |
0 |
58 |
0 |
1 |
2 |
222 |
| Evaluating heterogeneous forecasts for vintages of macroeconomic variables |
0 |
0 |
0 |
1 |
0 |
1 |
3 |
7 |
| Expert opinion versus expertise in forecasting |
0 |
0 |
0 |
19 |
0 |
0 |
1 |
111 |
| Experts' Stated Behavior |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
18 |
| Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter? |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
5 |
| Exploiting Spillovers to Forecast Crashes |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
24 |
| Fi-break Model of US Inflation Rate: Long-memory, Level Shifts, or Both? |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
44 |
| Fifty years since Koyck (1954)* |
0 |
0 |
1 |
60 |
0 |
0 |
2 |
208 |
| Financial volatility: an introduction |
0 |
0 |
0 |
748 |
0 |
0 |
1 |
1,867 |
| Forecasting Annual Inflation Using Weekly Money Supply |
0 |
1 |
4 |
7 |
0 |
1 |
8 |
16 |
| Forecasting Exchange Rates Using Neural Networks for Technical Trading Rules |
0 |
0 |
0 |
274 |
0 |
2 |
3 |
547 |
| Forecasting Real GDP Growth for Africa |
0 |
0 |
0 |
5 |
0 |
0 |
3 |
14 |
| Forecasting Social Conflicts in Africa Using an Epidemic Type Aftershock Sequence Model |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
12 |
| Forecasting aggregates using panels of nonlinear time series |
0 |
0 |
0 |
66 |
0 |
1 |
2 |
172 |
| Forecasting and seasonality |
0 |
0 |
0 |
55 |
0 |
0 |
0 |
233 |
| Forecasting economic and financial time-series with non-linear models |
0 |
0 |
0 |
288 |
1 |
1 |
6 |
761 |
| Forecasting house price growth rates with factor models and spatio-temporal clustering |
2 |
2 |
4 |
4 |
4 |
6 |
15 |
15 |
| Forecasting long memory left-right political orientations |
0 |
0 |
0 |
9 |
0 |
1 |
1 |
83 |
| Forecasting market shares from models for sales |
0 |
1 |
1 |
69 |
0 |
1 |
2 |
204 |
| Forecasting power-transformed time series data |
0 |
0 |
0 |
38 |
0 |
0 |
0 |
139 |
| Forecasting the levels of vector autoregressive log-transformed time series |
0 |
0 |
0 |
40 |
0 |
0 |
0 |
137 |
| Forecasting time series with long memory and level shifts |
0 |
0 |
0 |
59 |
0 |
1 |
1 |
173 |
| Forecasting time-varying arrivals: Impact of direct response advertising on call center performance |
0 |
0 |
2 |
7 |
0 |
0 |
2 |
22 |
| Forecasting unemployment using an autoregression with censored latent effects parameters |
0 |
0 |
0 |
58 |
0 |
0 |
2 |
189 |
| Forecasting: theory and practice |
0 |
2 |
13 |
54 |
5 |
19 |
114 |
348 |
| From first submission to citation: an empirical analysis |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
32 |
| Generalizations of the KPSS‐test for stationarity |
0 |
2 |
11 |
188 |
0 |
4 |
20 |
495 |
| Hemlines and the Economy: Which Goes Down First? |
3 |
5 |
21 |
107 |
6 |
16 |
46 |
295 |
| Heterogeneous Forecast Adjustment |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
13 |
| How Informative Are Earnings Forecasts? † |
0 |
0 |
0 |
4 |
1 |
1 |
2 |
39 |
| How accurate are government forecasts of economic fundamentals? The case of Taiwan |
0 |
0 |
0 |
13 |
0 |
1 |
1 |
142 |
| How do we pay with euro notes when some notes are missing? Empirical evidence from Monopoly® experiments |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
85 |
| How to deal with intercept and trend in practical cointegration analysis? |
0 |
0 |
0 |
285 |
0 |
1 |
2 |
629 |
| IGARCH and variance change in the US long-run interest rate |
0 |
0 |
0 |
119 |
1 |
1 |
1 |
301 |
| IMA(1,1) as a new benchmark for forecast evaluation |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
12 |
| INTRODUCTION TO THE SPECIAL ISSUE: NONLINEAR MODELING OF MULTIVARIATE MACROECONOMIC RELATIONS |
0 |
2 |
2 |
17 |
0 |
3 |
4 |
61 |
| Improving judgmental adjustment of model-based forecasts |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
32 |
| Impulse response functions for periodic integration |
0 |
0 |
0 |
15 |
1 |
3 |
3 |
126 |
| Inclusion of older annual data into time series models for recent quarterly data |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
4 |
| Incorporating Responsiveness to Marketing Efforts in Brand Choice Modeling |
0 |
0 |
0 |
17 |
1 |
1 |
1 |
95 |
| Incorporating judgment in forecasting models in times of crisis |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
4 |
| Increasing seasonal variation; unit roots versus shifts in mean and trend |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
9 |
| Inequality amongst the wealthiest and its link with economic growth |
0 |
0 |
0 |
14 |
0 |
1 |
4 |
55 |
| Inferring Transition Probabilities from Repeated Cross Sections |
0 |
0 |
0 |
2 |
0 |
1 |
2 |
10 |
| Inflation in Africa, 1960–2015 |
0 |
0 |
1 |
7 |
0 |
0 |
6 |
63 |
| Inflation in China, 1953-1978 |
0 |
0 |
1 |
1 |
0 |
0 |
4 |
6 |
| Inflation, forecast intervals and long memory regression models |
0 |
0 |
2 |
123 |
0 |
0 |
4 |
503 |
| Interaction Between Shelf Layout and Marketing Effectiveness and Its Impact on Optimizing Shelf Arrangements |
0 |
0 |
0 |
19 |
1 |
1 |
4 |
107 |
| Interpolation and correlation |
0 |
1 |
1 |
3 |
1 |
2 |
4 |
41 |
| Interpreting financial market crashes as earthquakes: A new Early Warning System for medium term crashes |
0 |
0 |
1 |
36 |
0 |
1 |
3 |
123 |
| Intertemporal Similarity of Economic Time Series: An Application of Dynamic Time Warping |
0 |
1 |
4 |
35 |
0 |
1 |
11 |
122 |
| Introduction to the special issue on new econometric models in marketing |
0 |
0 |
0 |
6 |
0 |
1 |
2 |
49 |
| Jury Report on the KVS Award for the Best Doctoral Thesis in Economics of the Academic Years 2006–2007 and 2007–2008 |
0 |
0 |
0 |
14 |
1 |
1 |
1 |
97 |
| Jury Report on the KVS Award for the Best Doctoral thesis in Economics of the Academic Years 2002/2003 and 2003/2004 |
0 |
0 |
0 |
20 |
0 |
1 |
2 |
116 |
| Jury Report on the Kvs Award for the Best Doctoral Thesis in Economics of the Academic Years 2004/2005 and 2005/2006 |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
52 |
| Large data sets in finance and marketing: introduction by the special issue editor |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
6 |
| Long memory and level shifts: Re-analyzing inflation rates |
0 |
0 |
0 |
165 |
0 |
2 |
2 |
908 |
| MODEL SELECTION IN PERIODIC AUTOREGRESSIONS |
0 |
0 |
0 |
9 |
0 |
1 |
3 |
33 |
| Marketing response and temporal aggregation |
0 |
0 |
0 |
5 |
0 |
3 |
5 |
16 |
| Mean shifts, unit roots and forecasting seasonal time series |
0 |
0 |
0 |
23 |
1 |
1 |
2 |
141 |
| Measurement Error in a First-order Autoregression |
0 |
0 |
0 |
17 |
0 |
1 |
2 |
68 |
| Merging models and experts |
0 |
0 |
0 |
16 |
0 |
0 |
0 |
58 |
| Model Selection in Periodic Autoregressions |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
177 |
| Model adequacy and influential observations |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
76 |
| Model selection for forecast combination |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
47 |
| Modeling Item Nonresponse in Questionnaires |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
26 |
| Modeling Judgment in Macroeconomic Forecasts |
0 |
0 |
0 |
1 |
1 |
2 |
3 |
9 |
| Modeling Multiple Regimes in the Business Cycle |
0 |
0 |
2 |
108 |
1 |
3 |
16 |
313 |
| Modeling Purchases as Repeated Events |
0 |
0 |
0 |
39 |
0 |
0 |
2 |
167 |
| Modeling Seasonality in New Product Diffusion |
0 |
0 |
0 |
12 |
1 |
1 |
1 |
96 |
| Modeling box office revenues of motion pictures✰ |
0 |
0 |
0 |
2 |
1 |
1 |
4 |
26 |
| Modeling consideration sets and brand choice using artificial neural networks |
0 |
0 |
0 |
7 |
0 |
1 |
3 |
67 |
| Modeling dynamic effects of promotion on interpurchase times |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
84 |
| Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve? |
0 |
0 |
1 |
5 |
0 |
1 |
2 |
31 |
| Modeling seasonality in bimonthly time series |
0 |
0 |
0 |
6 |
0 |
0 |
1 |
40 |
| Modeling the diffusion of scientific publications |
0 |
0 |
0 |
30 |
0 |
0 |
0 |
123 |
| Modelling and forecasting level shifts in absolute returns |
0 |
0 |
0 |
111 |
1 |
3 |
3 |
489 |
| Modelling day-of-the-week seasonality in the S&P 500 index |
1 |
1 |
1 |
202 |
1 |
2 |
3 |
727 |
| Modelling regional house prices |
0 |
0 |
1 |
38 |
0 |
1 |
6 |
124 |
| Model‐based forecast adjustment: With an illustration to inflation |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
16 |
| Moving average filters and periodic integration |
0 |
0 |
0 |
2 |
0 |
1 |
1 |
19 |
| Moving average filters and unit roots |
0 |
0 |
0 |
32 |
0 |
0 |
6 |
153 |
| Multiple unit roots in periodic autoregression |
0 |
0 |
1 |
73 |
0 |
1 |
4 |
197 |
| ON PHILLIPS–PERRON-TYPE TESTS FOR SEASONAL UNIT ROOTS |
0 |
0 |
0 |
19 |
0 |
1 |
4 |
72 |
| Off the Hook: Measuring the Impact of Mobile Telephone Use on Economic Development of Households in Uganda using Copulas |
0 |
0 |
1 |
16 |
0 |
0 |
2 |
42 |
| On Periodic Correlations between Estimated Seasonal and Nonseasonal Components in German and U.S. Unemployment |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
225 |
| On SETAR non-linearity and forecasting |
0 |
0 |
0 |
206 |
0 |
1 |
2 |
661 |
| On Seasonal Cycles, Unit Roots, And Mean Shifts |
1 |
1 |
1 |
109 |
1 |
1 |
1 |
314 |
| On data transformations and evidence of nonlinearity |
0 |
0 |
0 |
4 |
0 |
1 |
1 |
27 |
| On forecasting cointegrated seasonal time series |
0 |
0 |
1 |
38 |
0 |
1 |
6 |
126 |
| On forecasting exchange rates using neural networks |
0 |
0 |
0 |
122 |
0 |
0 |
0 |
307 |
| On inflation expectations in the NKPC model |
0 |
0 |
1 |
11 |
0 |
0 |
1 |
31 |
| On modeling panels of time series* |
0 |
0 |
0 |
8 |
0 |
0 |
0 |
38 |
| On the Econometrics of the Bass Diffusion Model |
0 |
0 |
0 |
144 |
0 |
0 |
3 |
362 |
| On the Role of Seasonal Intercepts in Seasonal Cointegration |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
10 |
| On the dynamics of business cycle analysis: editors' introduction |
0 |
0 |
0 |
56 |
0 |
0 |
0 |
209 |
| On the dynamics of business cycle analysis: editors' introduction |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
7 |
| On the econometrics of the geometric lag model |
0 |
0 |
0 |
57 |
0 |
0 |
3 |
208 |
| On the life cycles of successful rock bands |
0 |
0 |
0 |
0 |
0 |
2 |
4 |
5 |
| On the number of categories in an ordered regression model |
0 |
0 |
1 |
14 |
0 |
0 |
1 |
47 |
| On the sensitivity of unit root inference to nonlinear data transformations |
0 |
0 |
0 |
14 |
0 |
0 |
2 |
80 |
| On trends and constants in periodic autoregressions |
0 |
0 |
1 |
11 |
0 |
3 |
7 |
118 |
| One model and various experts: Evaluating Dutch macroeconomic forecasts |
1 |
1 |
1 |
13 |
2 |
2 |
5 |
118 |
| One model and various experts: Evaluating Dutch macroeconomic forecasts |
0 |
0 |
0 |
2 |
1 |
1 |
1 |
35 |
| Optimal Data Interval for Estimating Advertising Response |
0 |
0 |
0 |
8 |
0 |
0 |
1 |
53 |
| Ordered logit analysis for selectively sampled data |
0 |
0 |
0 |
41 |
0 |
0 |
0 |
119 |
| Outlier Detection in Cointegration Analysis |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
767 |
| Outlier robust analysis of long-run marketing effects for weekly scanning data |
0 |
0 |
0 |
46 |
0 |
2 |
3 |
205 |
| PREDICTION INTERVALS FOR EXPERT-ADJUSTED FORECASTS |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
40 |
| Panel design effects on response rates and response quality |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
30 |
| Periodic Cointegration: Representation and Inference |
0 |
1 |
1 |
157 |
0 |
3 |
4 |
411 |
| Periodic integration in quarterly UK macroeconomic variables |
0 |
0 |
0 |
12 |
0 |
0 |
0 |
79 |
| Progress and challenges in econometrics |
0 |
0 |
0 |
77 |
0 |
1 |
2 |
188 |
| Properties of expert adjustments on model-based SKU-level forecasts |
0 |
0 |
0 |
31 |
0 |
0 |
3 |
170 |
| Quarterly US Unemployment: Cycles, Seasons and Asymmetries |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
947 |
| RISK ATTITUDES IN THE BOARD ROOM AND COMPANY PERFORMANCE: EVIDENCE FOR AN EMERGING ECONOMY |
0 |
0 |
0 |
1 |
0 |
0 |
4 |
47 |
| Random‐coefficient periodic autoregressions |
0 |
0 |
0 |
5 |
0 |
0 |
2 |
38 |
| Recent Advances in Modelling Seasonality |
0 |
0 |
0 |
1 |
1 |
3 |
5 |
507 |
| Recognizing changing seasonal patterns using artificial neural networks |
0 |
0 |
0 |
39 |
1 |
2 |
4 |
119 |
| Recovering Historical Inflation Data from Postage Stamps Prices |
0 |
0 |
1 |
5 |
0 |
1 |
3 |
59 |
| Robust Inference on Average Economic Growth* |
0 |
0 |
0 |
4 |
0 |
1 |
2 |
69 |
| SETS, arbitrage activity, and stock price dynamics |
0 |
0 |
1 |
36 |
0 |
0 |
5 |
175 |
| SIMPLE BAYESIAN FORECAST COMBINATION |
0 |
0 |
0 |
5 |
1 |
1 |
3 |
28 |
| SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS |
0 |
3 |
15 |
2,457 |
3 |
12 |
45 |
4,793 |
| Seasonal Adjustment and the Business Cycle in Unemployment |
0 |
0 |
0 |
48 |
0 |
0 |
1 |
272 |
| Seasonality and Stochastic Trends in German Consumption and Income, 1960.1-1987.4 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
134 |
| Seasonality and non-linear price effects in scanner-data-based market-response models |
0 |
0 |
0 |
33 |
0 |
1 |
1 |
142 |
| Seasonality, non-stationarity and the forecasting of monthly time series |
0 |
0 |
0 |
135 |
0 |
0 |
0 |
311 |
| Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy* |
0 |
0 |
0 |
25 |
0 |
0 |
3 |
99 |
| Short patches of outliers, ARCH and volatility modelling |
0 |
0 |
0 |
37 |
0 |
1 |
1 |
211 |
| Shrinkage estimators for periodic autoregressions |
0 |
0 |
1 |
1 |
0 |
2 |
5 |
5 |
| Size and value effects in Suriname |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
79 |
| Some comments on seasonal adjustment |
0 |
0 |
0 |
58 |
0 |
0 |
2 |
209 |
| Specification Testing in Hawkes Models* |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
26 |
| Spurious deterministic seasonality |
0 |
0 |
0 |
30 |
0 |
1 |
2 |
116 |
| Spurious principal components |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
17 |
| Statistical institutes and economic prosperity |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
33 |
| Structural breaks and long memory in US inflation rates: Do they matter for forecasting? |
0 |
0 |
0 |
29 |
0 |
0 |
0 |
100 |
| THE CASH USE OF THE MALAYSIAN RINGGIT: CAN IT BE MORE EFFICIENT? |
0 |
0 |
1 |
3 |
1 |
1 |
3 |
33 |
| THIS TIME IT IS DIFFERENT! OR NOT? DISCOUNTING PAST DATA WHEN PREDICTING THE FUTURE |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
42 |
| Temporal aggregation in a periodically integrated autoregressive process |
0 |
0 |
0 |
1 |
0 |
1 |
4 |
44 |
| Testing bias in professional forecasts |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
7 |
| Testing earnings management |
0 |
0 |
0 |
12 |
0 |
0 |
0 |
52 |
| Testing for ARCH in the Presence of Additive Outliers |
0 |
0 |
0 |
213 |
0 |
1 |
2 |
791 |
| Testing for Bias in Forecasts for Independent Multinomial Outcomes |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
| Testing for Seasonal Unit Roots in Monthly Panels of Time Series |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
82 |
| Testing for Smooth Transition Nonlinearity in the Presence of Outliers |
0 |
0 |
0 |
0 |
1 |
2 |
4 |
516 |
| Testing for Unit Roots and Non‐linear Transformations |
0 |
0 |
0 |
6 |
0 |
1 |
2 |
27 |
| Testing for bias in forecasts for independent binary outcomes |
0 |
0 |
1 |
2 |
0 |
0 |
2 |
12 |
| Testing for common deterministic trend slopes |
0 |
0 |
0 |
48 |
0 |
1 |
1 |
232 |
| Testing for convergence in left-right ideological positions |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
14 |
| Testing for harmonic regressors |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
43 |
| Testing for periodic integration |
0 |
0 |
0 |
38 |
0 |
1 |
3 |
170 |
| Testing for seasonality |
0 |
0 |
1 |
87 |
0 |
0 |
2 |
227 |
| Testing periodically integrated autoregressive models |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
33 |
| The Econometric Analysis of Seasonal Time Series |
0 |
0 |
0 |
2 |
1 |
1 |
3 |
10 |
| The Econometric Modelling of Financial Time Series: Second Edition, Terence C. Mills, (Cambridge: Cambridge University Press, 1999) 380 pages, Paperback; ISBN 0521-62492-4 ($27.95). Hardback: ISBN 0521-62413-4 ($80.00) |
0 |
0 |
0 |
151 |
0 |
0 |
1 |
354 |
| The Effects of Additive Outliers on Tests for Unit Roots and Cointegration |
0 |
0 |
0 |
0 |
1 |
1 |
5 |
625 |
| The M3 competition: Statistical tests of the results |
0 |
2 |
4 |
155 |
0 |
2 |
9 |
423 |
| The Norwegian Consumption Function: A Comment |
0 |
0 |
0 |
0 |
0 |
2 |
4 |
96 |
| The Stock Exchange of Suriname: Returns, Volatility, Correlations, and Weak-Form Efficiency |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
25 |
| The detection of observations possibly influential for model selection |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
18 |
| The diffusion of marketing science in the practitioners' community: opening the black box |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
4 |
| The diffusion of scientific publications: The case of Econometrica, 1987 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
12 |
| The effect of rounding on payment efficiency |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
62 |
| The effectiveness of high-frequency direct-response commercials |
0 |
0 |
0 |
6 |
0 |
0 |
2 |
25 |
| The effects of seasonally adjusting a periodic autoregressive process |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
39 |
| The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production |
0 |
0 |
1 |
74 |
0 |
1 |
3 |
275 |
| The impact of adoption timing on new service usage and early disadoption |
0 |
0 |
1 |
7 |
0 |
1 |
3 |
31 |
| The late 1970s bubble in Dutch collectible postage stamps |
0 |
0 |
0 |
4 |
0 |
2 |
5 |
50 |
| The life cycle of social media |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
59 |
| Trends in three decades of rankings of Dutch economists |
0 |
0 |
0 |
2 |
1 |
1 |
3 |
11 |
| Twenty years of cointegration |
0 |
0 |
0 |
43 |
0 |
0 |
1 |
90 |
| UNIT ROOTS IN PERIODIC AUTOREGRESSIONS |
0 |
0 |
0 |
3 |
1 |
1 |
2 |
16 |
| Unit roots in the Nelson-Plosser data: Do they matter for forecasting? |
0 |
0 |
0 |
87 |
0 |
0 |
0 |
244 |
| VOLATILITY TRANSMISSION AND PATTERNS IN BUND FUTURES |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
15 |
| Visualizing time-varying correlations across stock markets |
0 |
0 |
2 |
121 |
0 |
0 |
2 |
261 |
| When Do Price Thresholds Matter in Retail Categories? |
0 |
1 |
1 |
21 |
1 |
3 |
4 |
70 |
| Why is GDP typically revised upwards? |
0 |
0 |
0 |
12 |
0 |
0 |
2 |
49 |
| “Panelizing” Repeated Cross Sections |
0 |
0 |
0 |
6 |
0 |
0 |
1 |
37 |
| Total Journal Articles |
12 |
37 |
163 |
13,930 |
66 |
272 |
901 |
48,281 |