书名:
Python Programming for Quantitative Economics
发布时间:April 7, 2020
目录:
I Tools and Techniques 1
1 Geometric Series for Elementary Economics 3
2 Linear Algebra 23
3 Complex Numbers and Trigonometry 47
4 LLN and CLT 57
5 Heavy-Tailed Distributions 75
II Introduction to Dynamics 93
6 Dynamics in One Dimension 95
7 AR1 Processes 115
8 Finite Markov Chains 129
9 Inventory Dynamics 153
10 Linear State Space Models 163
11 Application: The Samuelson Multiplier-Accelerator 187
12 Kesten Processes and Firm Dynamics 221
13 Wealth Distribution Dynamics 235
14 A First Look at the Kalman Filter 251
15 Shortest Paths 269
III Search 279
16 Job Search I: The McCall Search Model 281
17 Job Search II: Search and Separation 297
18 Job Search III: Fitted Value Function Iteration 311
19 Job Search IV: Correlated Wage Offers 321
20 Job Search V: Modeling Career Choice 331
21 Job Search VI: On-the-Job Search 345
IV Consumption, Savings and Growth 357
22 Cake Eating I: Introduction to Optimal Saving 359
23 Cake Eating II: Numerical Methods 371
24 Optimal Growth I: The Stochastic Optimal Growth Model 387
25 Optimal Growth II: Accelerating the Code with Numba 405
26 Optimal Growth III: Time Iteration 417
27 Optimal Growth IV: The Endogenous Grid Method 429
28 The Income Fluctuation Problem 437
V Information 453
29 Job Search VII: Search with Learning 455
30 A Problem that Stumped Milton Friedman 483
31 Exchangeability and Bayesian Updating 501
32 Likelihood Ratio Processes 517
VI LQ Control 535
33 LQ Control: Foundations 537
34 The Permanent Income Model 567
35 Permanent Income II: LQ Techniques 585
36 Production Smoothing via Inventories 603
VII Multiple Agent Models 623
37 Schelling’s Segregation Model 625
38 A Lake Model of Employment and Unemployment 637
39 Rational Expectations Equilibrium 663
40 Stability in Linear Rational Expectations Models 679
41 Markov Perfect Equilibrium 701
42 Uncertainty Traps 719
43 The Aiyagari Model 733
VIII Asset Pricing and Finance 743
44 Asset Pricing: Finite State Models 745
45 Asset Pricing with Incomplete Markets 767
IX Data and Empirics 779
46 Pandas for Panel Data 781
47 Linear Regression in Python 803
48 Maximum Likelihood Estimation 821