Currency Unions and Trade: A PPML Re-assessment with High-dimensional Fixed Effects

被引:127
|
作者
Larch, Mario [1 ,2 ]
Wanner, Joschka [3 ]
Yotov, Yoto V. [4 ]
Zylkin, Thomas [5 ]
机构
[1] Univ Bayreuth, CEPII, CESifo, Univ Str 30, D-95447 Bayreuth, Germany
[2] Ifo Inst, Univ Str 30, D-95447 Bayreuth, Germany
[3] Univ Bayreuth, Univ Str 30, D-95447 Bayreuth, Germany
[4] Drexel Univ, Ifo Inst, CESifo, ERI BAS, 1020 G Hall,3200 Market St, Philadelphia, PA 19104 USA
[5] Univ Richmond, Robins Sch Business, 1 Gateway Rd, Richmond, VA 23217 USA
关键词
GRAVITY; MODELS; AGREEMENTS; EURO; EMU; HETEROGENEITY; POISSON; MEMBERS; HONEY; LOG;
D O I
10.1111/obes.12283
中图分类号
F [经济];
学科分类号
02 ;
摘要
Recent work on the effects of currency unions (CUs) on trade stresses the importance of using many countries and years in order to obtain reliable estimates. However, for large samples, computational issues associated with the three-way (exporter-time, importer-time, and country pair) fixed effects currently recommended in the gravity literature have heretofore limited the choice of estimator, leaving an important methodological gap. To address this gap, we introduce an iterative poisson pseudo-maximum likelihood (PPML) estimation procedure that facilitates the inclusion of these fixed effects for large data sets and also allows for correlated errors across countries and time. When applied to a comprehensive sample with more than 200 countries trading over 65 years, these innovations flip the conclusions of an otherwise rigorously specified linear model. Most importantly, our estimates for both the overall CU effect and the Euro effect specifically are economically small and statistically insignificant. We also document that linear and PPML estimates of the Euro effect increasingly diverge as the sample size grows.
引用
收藏
页码:487 / 510
页数:24
相关论文
共 50 条
  • [31] PERFORMANCE ASSESSMENT OF HIGH-DIMENSIONAL VARIABLE IDENTIFICATION
    Yu, Yanjia
    Yang, Yi
    Yang, Yuhong
    STATISTICA SINICA, 2022, 32 (02) : 695 - 718
  • [32] UNIFORM INFERENCE IN HIGH-DIMENSIONAL DYNAMIC PANEL DATA MODELS WITH APPROXIMATELY SPARSE FIXED EFFECTS
    Kock, Anders Bredahl
    Tang, Haihan
    ECONOMETRIC THEORY, 2019, 35 (02) : 295 - 359
  • [33] HIGH-DIMENSIONAL INFERENCE FOR DYNAMIC TREATMENT EFFECTS
    Bradic, Jelena
    Ji, Weijie
    Zhang, Yuqian
    ANNALS OF STATISTICS, 2024, 52 (02): : 415 - 440
  • [34] Dimensional and dynamic effects of common currency on trade: The case of the African Franc Zone
    Mignamissi, Dieudonne
    Mouhamed, Mbouandi Njikam
    JOURNAL OF INTERNATIONAL TRADE & ECONOMIC DEVELOPMENT, 2022, 31 (08): : 1243 - 1280
  • [35] Robustness Assessment of High-Dimensional Jump Linear system
    Shishkin, Serge L.
    49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2010, : 6487 - 6492
  • [36] A Re-Assessment of Positive Selection on Mitochondrial Genomes of High-Elevation Phrynocephalus Lizards
    Atlas, Jared E.
    Fu, Jinzhong
    JOURNAL OF MOLECULAR EVOLUTION, 2021, 89 (1-2) : 95 - 102
  • [37] Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
    Letham, Benjamin
    Calandra, Roberto
    Rai, Akshara
    Bakshy, Eytan
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 33, NEURIPS 2020, 2020, 33
  • [38] A Re-Assessment of Positive Selection on Mitochondrial Genomes of High-Elevation Phrynocephalus Lizards
    Jared E. Atlas
    Jinzhong Fu
    Journal of Molecular Evolution, 2021, 89 (1-2) : 95 - 102
  • [39] A Re-Assessment of Positive Selection on Mitochondrial Genomes of High-Elevation Phrynocephalus Lizards
    Atlas, Jared E.
    Fu, Jinzhong
    JOURNAL OF MOLECULAR EVOLUTION, 2021, : 95 - 102
  • [40] Nested effects models for high-dimensional phenotyping screens
    Markowetz, Florian
    Kostka, Dennis
    Troyanskaya, Olga G.
    Spang, Rainer
    BIOINFORMATICS, 2007, 23 (13) : I305 - I312