1Part 1
140Flexible and strict rules
2Part II
141Smoothing
31.1 The case for macro-econometric models
142Open economy rules
41.2 Methodological issues
143Real-time interest rate rules
51.3 The supply-side and wage- and price-setting
144Comparing the rules
61.4 The transmission mechanism
14510.3.3 Relative loss calculations
71.5 Summary
14610.3.4 Welfare losses evaluated by response surface estimation
81.6 Exercise
14710.4 Summary
9References: Figure Resource
14810.5 Exercise
102.1 Introduction: small vs. large models
149References: Figure Resource
112.2 The roles of statistics and economic theory in macro-econometrics
15011.1 Introduction
122.2.1 The influx of statistics into economics
15111.2 EqCMs vs. dVARs in macro-econometric forecasting
132.2.2 Role of economic theory in macro-econometrics
15211.2.1 Forecast errors of bivariate EqCMs and dVARs
142.3 Identifying partial structure in submodels
153A simple DGP
152.3.1 The theory of reduction
154EqCM and dVAR models of the DGP
162.3.2 Congruence
155Parameter change after the forecast is prepared
172.4 An example: modeling the household sector
156Change in the equilibrium-correction coefficient α
182.4.1 The aggregate consumption function
157Parameter change before the forecast is made
192.4.2 Rival models
158Change in the intercept ζ
202.5 Is modeling subsystems and combining them to a global model a viable procedure?
159Estimated parameters
212.6 Summary
160Discussion
222.7 Exercise: References
16111.2.2 A large-scale EqCM model and four dVAR type forecasting systems based on differenced data
233.1 Introduction
162The incumbent EqCM model—eRIM
243.2 Cointegration
163Two full-scale dVAR models—dRIM and dRIMc
253.2.1 Causality
164Two univariate models—dAR and dARr
263.2.2 Steady-state growth
165Relative forecast performance 1992–1994
273.2.3 Early empiricism
16611.3 Model specification and forecast accuracy
283.3 Summary
16711.3.1 Forecast errors of stylized inflation models
293.4 Exercise
16811.3.2 Revisiting empirical models of Norwegian inflation
30References: Figure Resource
169The dynamic ICM
314.1 Introduction: 4.1.1 Lineages of the Phillips curve
170The PCM
324.2 Cointegration, causality, and the Phillips curve natural rate
17111.3.3 Forecast comparisons
334.3 Is the Phillips curve consistent with persistent changes in unemployment?
17211.4 Summary
344.4 Estimating the uncertainty of the Phillips curve NAIRU
17311.5 Exercise
354.5 Inversion and the Lucas critique
174References: Figure Resource
364.5.1 Inversion
1751.1 Concepts of Stochastic Dominance
374.5.2 Lucas critique
1761.1.1 Definitions
384.5.3 Model-based vs. data-based expectations
177First-Order Stochastic Dominance (FSD)
394.5.4 Testing the Lucas critique
178Definition 1.1.1
404.6 An empirical open economy Phillips curve system
179Second-Order Stochastic Dominance (SSD) : Definition 1.1.2
414.7 Summary
180Higher-Order Stochastic Dominance
424.8 Exercise
181Equivalence of the Definitions
43References: Figure Resource
1821.1.2 Basic Properties of Stochastic Dominance: Theorem 1.1.4
445.1 Introduction
1831.2 Applications of Stochastic Dominance
455.2 Wage bargaining and monopolistic competition
1841.2.1 Welfare Analysis
465.3 The wage curve NAIRU
1851.2.2 Finance
475.4 Cointegration and identification
1861.2.3 Labor Economics
485.5 Cointegration and Norwegian manufacturing wages
1871.2.4 International Economics
495.6 Aggregate wages and prices: UK quarterly data
1881.2.5 Health Economics
505.7 Summary
1891.2.6 Agricultural Economics
515.8 Exercise: References
1901.3 Summary
526.1 Introduction
1911.4 Exercise
536.2 Nominal rigidity and equilibrium correction
192References: Figure Resource
546.3 Stability and steady-state
1932.1 Introduction
556.4 The stable solution of the conditional wage-price system
1942.2 Null of Dominance against Non-Dominance
566.4.1 Cointegration, long-run multipliers, and the steady-state
1952.2.1 Tests Based on Multiple Comparisons: (1) Anderson Test
576.4.2 Nominal rigidity despite dynamic homogeneity
1962.2.2 Neyman’s Smooth Tests
586.4.3 An important unstable solution: the ‘no wedge’ case
1972.3 Null of Non-Dominance against Dominance
596.4.4 A main-course interpretation
1982.4 Testing for Monday Effects in Stock Markets
606.5 Comparison with the wage-curve NAIRU
1992.5 Summary
616.6 Comparison with the wage Phillips curve NAIRU
2002.6 Exercise: References
626.7 Do estimate wage-price models support the NAIRU view of equilibrium unemployment?
2013.1 Stochastic Dominance Tests with Improved Power
636.8 Econometric evaluation of Nordic structural employment estimates
2023.1.1 The Contact Set Approach: Example 3.1
646.9 Beyond the natural rate doctrine: unemployment–inflation dynamics
2033.2 Program Evaluation and Stochastic Dominance
656.10 Summary
2043.2.1 Distributional Treatment Effects
666.11 Exercise
205Potential Outcome Framework
67References: Figure Resource
206Definition 3.2.1
687.1 Introduction
207Inference under Rank Preservation
697.2 The NPCM defined
208Assumption 3.2.1
707.3 NPCM as a system
209Theorem 3.2.1:
717.4 Sensitivity analysis
210Inference with Repeated Measurements
727.5 Testing the specification
211Assumption 3.2.2
737.5.1 An encompassing representation
2123.2.2 Counterfactual Policy Analysis: Theorem 3.2.3
747.5.2 Testing against richer dynamics
2133.3 Some Issues of Stochastic Dominance Tests
757.5.3 Evaluation of the system
2143.3.1 Stochastic Dominance Tests with Unbounded Supports
767.5.4 Testing the encompassing implications
2153.3.2 Classification of Stochastic Dominance Relations
777.6 Summary
2163.3.3 Large Deviation Approximation
787.7 Exercise: References
2173.4 Empirical Examples
798.1 Introduction
2183.4.1 Distributional Treatment Effects of Veteran Status
808.2 Models of money demand
2193.4.2 Returns to Schooling: Quantile Treatment Effects
818.2.1 The velocity of circulation
2203.5 Summary
828.2.2 Dynamic models
2213.6 Exercise
838.2.3 Inverted money demand equations
222References: Figure Resource
848.3 Monetary analysis of Euro-area data
2234.1 Introduction
858.3.1 Money demand in the Euro area 1980–97
2244.2 Conditional Stochastic Dominance at Fixed Values of Covariates: 4.2.1 Quantile-Based Tests
868.3.2 Inversion may lead to forecast failure
2254.3 Conditional Stochastic Dominance at All Values of Covariates
878.4 Monetary analysis of Norwegian data
2264.3.1 The Poissonization Approach
888.4.1 Money demand in Norway—revised and extended data
2274.3.2 The Unconditional Moment Representation Approach
89Re-estimating a money demand model for Norway
2284.4 Stochastic Monotonicity
90An improved model for the period 1969–2001
2294.5 Empirical Examples
918.4.2 Monetary effects in the inflation equation?
2304.5.1 Testing for Conditional Treatment Effects: The main features of the LWY test are as follows: they
928.5 Inflation models for the Euro area
2314.6 Summary
938.5.1 The wage-price block of the Area Wide Model
2324.7 Exercise: References
948.5.2 The Incomplete Competition Model
2335.1 Multivariate Stochastic Dominance
958.5.3 The New Keynesian Phillips Curve Model
2345.2 Analysis of Economic Inequality and Poverty
968.5.4 The P∗-model of inflation
2355.2.1 Lorenz Dominance: BDB consider two sampling schemes:
978.6 Empirical evidence from Euro-area data
2365.2.2 Poverty Dominance
988.6.1 The reduced form AWM inflation equation
2375.2.3 Initial Dominance: Definition 5.2.3
998.6.2 The reduced form ICM inflation equation
2385.3 Analysis of Portfolio Choice Problems
1008.6.3 The P∗-model
2395.3.1 Marginal Conditional Stochastic Dominance
1018.6.4 The New Keynesian Phillips curve
2405.3.2 Stochastic Dominance Efficiency: Definition 5.3.1 (SSD Efficiency)
1028.6.5 Evaluation of the inflation models’ properties
2415.4 Weaker Notions of Stochastic Dominance
1038.6.6 Comparing the forecasting properties of the models
2425.4.1 Almost Stochastic Dominance
1048.6.7 Summary of findings—Euro-area data
2435.4.2 Infinite-Order Stochastic Dominance
1058.7 Empirical evidence for Norway
2445.5 Related Concepts of Stochastic Dominance
1068.7.1 The Incomplete Competition Model
2455.5.1 Density Ratio Dominance
1078.7.2 The New Keynesian Phillips curve
2465.5.2 Positive Quadrant Dependence
1088.7.3 Inflation equations derived from the P∗-model
247Definition 5.5.2
1098.7.4 Testing for neglected monetary effects on inflation
248Theorem 5.5.2
1108.7.5 Evaluation of inflation models’ properties
249Theorem 5.5.3
1118.7.6 Comparing the forecasting properties of the models
2505.6 Summary
1128.8 Summary
2515.7 Exercise: References
1138.9 Exercise
252A.1 The Lucas critique
114References: Figure Resource
253A.2 Solving and estimating rational expectations models
1159.1 Introduction
254A.2.1 Repeated substitution
1169.2 The wage-price model
255Find Etπt+1
1179.2.1 Modelling the steady-state
256Solve for πt
1189.2.2 The dynamic wage-price model
257A.2.2 Undetermined coefficients
1199.3 Closing the model: marginal models for feedback variables
258A.2.3 Factorization
1209.3.1 The nominal exchange rate vt
259A.2.4 Estimation
1219.3.2 Mainland GDP output yt
260A.2.5 Does the MA (1) process proves that the forward solution applies?
1229.3.3 Unemployment ut
261A.3 Calculation of interim multipliers in a linear dynamic model: a general exposition
1239.3.4 Productivity at Growth
262A
1249.3.5 Credit expansion crt
263C
1259.3.6 Interest rates for government bonds RBOt and bank loans RLt
264D
1269.4 Testing exogeneity and invariance
265E
1279.5 Model performance
266F
1289.6 Responses to a permanent shift in interest rates
267H
1299.7 Summary
268I
1309.8 Exercise
269L
131References: Figure Resource
270M
13210.1 Introduction
271N
13310.2 Four groups of interest rate rules
272P
13410.2.1 Revisions of output data: a case for real-time variables?
273Q
13510.2.2 Data input for interest rate rules
274R
13610.2.3 Ex post calculated interest rate rules
275S
13710.3 Evaluation of interest rate rules
276S
13810.3.1 A new measure—RMSTEs
277U
13910.3.2 RMSTEs and their decomposition
278V
