The Japanese economy in crises: A time series segmentation study

Economics

Volumn 6, Issue , 2012, Pages

  Cheong, Siew Ann ^a   Fornia, Robert Paulo ^b   Lee, Gladys Hui Ting ^a   Kok, Jun Liang ^a   Yim, Woei Shyr ^a   Xu, Danny Yuan ^c   Zhang, Yiting ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b UNIVERSITY OF COLORADO   (United States)

^c BARD COLLEGE   (United States)

Author keywords

Clustering; Cross correlations; Economic recovery; Financial crisis; Financial time series; Japanese industries; Macroeconomic cycle; Minimal spanning tree; Segmentation

Indexed keywords

EID: 84865082014     PISSN: None     EISSN: 18646042     Source Type: Journal    
DOI: 10.5018/economics-ejournal.ja.2012-5     Document Type: Article

References (139)

1. Amyx, J. (2004). Japan's financial crisis: Institutional rigidity and reluctant change. Princeton University Press.
2. Andrews, D. (2005). Cross-section regression with common shocks. Econometrica, 73(5): 1551-1585. URL http://ideas.repec.org/a/ecm/emetrp/v73y2005i5p1551-1585.html.
3. Bai, J. (1994). Least squares estimation of a shift in linear processes. Journal of Time Series Analysis, 15(5): 453-472. URL http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.1994.tb00204.x/abstract.
4. Bai, J. (1995). Least absolute deviation estimation of a shift. Econometric Theory, 11(3): 403-436. URL http://econpapers.repec.org/article/cupetheor/v_3a11_3ay_3a1995_3ai_3a03_3ap_3a403-436_5f00.htm.
5. Bai, J. (1997). Estimation of a change point in multiple regression models. The Review of Economics and Statistics, 79(4): 551-563. URL http://ideas.repec.org/a/tpr/restat/v79y1997i4p551-563.html.
6. Bai, J. (2009). Panel data models with interactive fixed effects. Econo-metrica, 77(4): 1229-1279. URL http://ideas.repec.org/a/ecm/emetrp/v77y2009i4p1229-1279.html.
7. Bai, J., and Carrion-i-Silvestre, J. (2009). Structural changes, common stochastic trends, and unit roots in panel data. Review of Economic Studies, 76(2): 471-501. URL http://ideas.repec.org/a/bla/restud/v76y2009i2p471-501.html.
8. Bai, J., Lumsdaine, R., and Stock, J. H. (1998). Testing for and dating common breaks in multivariate time series. Review of Economic Studies, 65(3): 395-432. URL http://ideas.repec.org/a/bla/restud/v65y1998i3p395-432.html.
9. Bai, J., and Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1): 47-78. URL http://ideas.repec.org/a/ecm/emetrp/v66y1998i1p47-78.html.
10. Bai, J., and Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1): 1-21. URL http: //ideas.repec.org/a/jae/japmet/v18y2003i1p1-22.html.
11. Baker, F. (1972). Numerical taxonomy for educational researchers. Review of Educational Research, 42(3): 345-358. URL http://rer.sagepub.com/content/42/3/345.full.pdf.
12. Baker, F. (1974). Stability of two hierarchical grouping techniques case 1: Sensi-tivity to data errors. Journal of the American Statistical Association, 69(346): 440-445. URL http://www.jstor.org/stable/2285675.
13. Barberis, N., Shleifer, A., and Wurgler, J. (2005). Comovement. Journal of Financial Economics, 75(2): 283-317. URL http://ideas.repec.org/a/eee/jfinec/v75y2005i2p283-317.html.
14. Barndorff-Nielsen, O., and Shepard, N. (2006). Econometrics of testing for jumps in financial economics using bipower variation. Journal of Financial Econometrics, 4(1): 1-30. URL http://ideas.repec.org/a/oup/jfinec/v4y2006i1p1-30.html.
15. Baur, D., and Lucey, B. (2009). Flights and contagion - An empirical analysis of stock-bond correlations. Journal of Financial Stability, 5(4): 339-352. URL http://ideas.repec.org/a/eee/finsta/v5y2009i4p339-352.html.
16. Baur, D., and Lucey, B. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds, and gold. The Financial Review, 45(2): 217-229. URL http://ideas.repec.org/a/bla/finrev/v45y2010i2p217-229.html.
17. Baxter, M., and Kouparitsas, M. (2005). Determinants of business cycle comovement: A robust analysis. Journal of Monetary Economics, 52(1): 113-157. URL http://ideas.repec.org/a/eee/moneco/v52y2005i1p113-157.html.
18. Bayoumi, T. (2001). The morning after: explaining the slowdown in Japanese growth in the 1990s. Journal of International Economics, 53(2): 241-259. URL http://ideas.repec.org/a/eee/inecon/v53y2001i2p241-259.html.
19. Bernaola-Galván, P., Román-Roldán, R., and Oliver, J. (1996). Compositional segmentation and long-range fractal correlations in DNA sequences. Physical Review E, 53(5): 5181-5189. URL http://linkage.rockefeller.edu/wli/moved.8.04/dna_corr/bernaola96.pdf.
20. Bigsten, A. (2005). Can Japan make a comeback? The World Economy, 28(4): 595-606. URL http://ideas.repec.org/a/bla/worlde/v28y2005i4p595-606.html.
21. Boginski, V., Butenko, S., and Pardalos, P. (2005). Statistical analysis of financial networks. Computational Statistics & Data Analysis, 48(2): 431-443. URL http://ideas.repec.org/a/eee/csdana/v48y2005i2p431-443.html.
22. Bollerslev, T., Law, T., and Tauchen, G. (2008). Risk, jumps, and diversification. Journal of Econometrics, 144(1): 234-256. URL http://ideas.repec.org/a/eee/econom/v144y2008i1p234-256.html.
23. Bonanno, G., Caldarelli, G., Lillo, F., and Mantegna, R. (2003). Topology of correlation-based minimal spanning trees in real and model markets. Physical Review E, 68(4): 046130. DOI 10.1103/PhysRevE.68.046130. URL http://link.aps.org/doi/10.1103/PhysRevE.68.046130.
24. Bonanno, G., Caldarelli, G., Lillo, F., Miccichè, S., Vandewalle, N., and Mantegna, R. (2004). Networks of equities in financial markets. The European Physical Journal B, 38(2): 363-371. URL http://www.springerlink.com/content/9v2k3000052etkr3/.
25. Bonanno, G., Vandewalle, N., and Mantegna, R. (2000). Taxonomy of stock market indices. Physical Review E, 62(6): R7615-R7618. URL http://econpapers.repec. org/paper/arxpapers/cond-mat_2f0001268.htm.
26. Borghesi, C., Marsili, M., and Miccichè, S. (2007). Emergence of time-horizon invariant correlation structure in financial returns by subtraction of the market mode. Physical Review E, 76(2): 026104. URL http://ideas.repec.org/p/arx/papers/physics-0702106.html.
27. Brida, J., and Risso, W. (2007). Dynamics and structure of the main Italian companies. International Journal of Modern Physics C, 18(11): 1783-1793. RL http://papers.ssrn.com/sol3/papers.cfm?abstract_id=101604
28. Brida, J., and Risso, W. (2008). Multidimensional minimal spanning tree: The Dow Jones case. Physica A, 387(21): 5205-5210. URL http://www.sciencedirect.com/science/article/pii/S0378437108004299.
29. Brida, J. G., and Risso, W. A. (2010). Dynamics and structure of the 30 largest North American companies. Computational Economics, 35(1): 85-99. URL http://ideas.repec.org/a/kap/compec/v35y2010i1p85-99.html.
30. Canova, F., and Marrinan, J. (1998). Sources and propagation of interna- tional output cycles: Common shocks or transmission? Journal of Interna- tional Economics, 46(1): 133-166. URL http://ideas.repec.org/a/eee/inecon/v46y1998i1p133-166.html.
31. Carrion-i-Silvestre, J., Barrio-Castro, T. D., and López-Bazo, E. (2005). Breaking the panels: An application to the GDP per capita. Econometrics Journal, 8(2): 159-175. URL http://ideas.repec.org/a/ect/emjrnl/v8y2005i2p159-175.html.
32. Carrion-i-Silvestre, J., Kim, D., and Perron, P. (2009). GLS-based unit root tests with multiple structural breaks under both the null and the alternative hypotheses. Econometric Theory, 25(6): 1754-1792. URL http://ideas.repec.org/a/cup/etheor/v25y2009i06p1754-1792_99.html.
33. Çukur, S., Eryiǧit, M., and Eryiǧit, R. (2007). Cross cor-relations in an emerging market financial data. Physica A, 376: 555-564. URL http://www.mendeley.com/research/darboux-theorems-and-wronskian-formulas-for-integrable-systems-i-constrained-kp-flows/.
34. Cheong, S.-A., Stodghill, P., Schneider, D., Cartinhour, S., and Myers, C. (2009a). Extending the recursive Jensen-Shannon segmentation of biological sequences. URL http://arxiv.org/PS_cache/arxiv/pdf/0904/0904.2466v1.pdf.Q-bio/0904.2466.
35. Cheong, S.-A., Stodghill, P., Schneider, D., Cartinhour, S., and Myers, C. R. (2009b). The context sensitivity problem in biological sequence segmentation. URL http://arxiv.org/abs/0904.2668. Q-bio/0904.2668.
36. Cheung, W., Fung, S., and Tsai, S.-C. (2010). Global capital market interde-pendence and spillover effect of credit risk: evidence from the 2007-2009 global financial crisis. Applied Financial Economics, 20(1): 85-103. URL http://ideas.repec.org/a/taf/apfiec/v20y2010i1-2p85-103.html.
37. Chong, T.-L. (1995). Partial parameter consistency in a misspecified structural change model. Economics Letters, 49(4): 351-357. URL http://ideas.repec.org/a/eee/ecolet/v49y1995i4p351-357.html.
38. Chong, T.-L. (2001). Structural change in AR(1) models. Econometric Theory, 17(1): 87-155. URL http://ideas.repec.org/a/cup/etheor/v17y2001i01p87-155_17.html.
39. Coelho, R., Gilmore, C., Lucey, B., Richmond, P., and Hutzler, S. (2007a). The evolution of interdependence in world equity markets - Evidence from mini- mum spanning trees. Physica A, 376: 455-466. URL http://arxiv.org/abs/physics/0607022.
40. Coelho, R., Hutzler, S., Repetowicz, P., and Richmond, P. (2007b). Sector analysis for a FTSE portfolio of stocks. Physica A, 373: 615-626. URL http://arxiv.org/abs/physics/0601189.
41. Connolly, R., Stivers, C., and Sun, L. (2005). Stock market uncertainty and the stock-bond return relation. Journal of Financial and Quantitative Analysis, 40(1): 161-194. URL http://www.jstor.org/stable/27647190.
42. Connolly, R., Stivers, C., and Sun, L. (2007). Commonality in the time-variation of stock-stock and stock-bond return comovements. Journal of Financial Markets, 10(2): 192-218. URL http://ideas.repec.org/a/eee/finmar/v10y2007i2p192-218.html.
43. Croux, C., Forni, M., and Reichlin, L. (2001). A measure of comovement for economic variables: Theory and empirics. Review of Economics and Statistics, 83(2): 232-241. URL http://ideas.repec.org/a/tpr/restat/v83y2001i2p232-241.html.
44. Duch, J., and Arenas, A. (2005). Community detection in complex networks using extremal optimization. Physical Review E, 72(2): 027104. DOI http://arxiv.org/abs/cond-mat/0501368.
45. Eng, L. (Apr 2010). Financial Time Series Segmentation Based on Lévy Stable Distributions. Master's thesis, Nanyang Technological University.
46. Eom, C., Oh, G., Jung, W.-S., Jeong, H., and Kim, S. (2009). Topological properties of stock networks based on minimal spanning tree and random matrix theory in financial time series. Physica A, 388: 900-906. URL http://www.sciencedirect.com/science/article/pii/S0378437108009862.
47. Eryiǧit, M., and Eryiǧit, R. (2009). Network structure of cross-correlations among the world market indices. Physica A, 388: 3551-3562. URL http://dkydros.files.wordpress.com/2010/02/turkey-pmfg.pdf.
48. Fama, E., and Roll, R. (1971). Parameter estimates for symmetric stable distribu- tions. Journal of the American Statistical Association, 66(334): 331-338. URL http://www.jstor.org/stable/2283932.
49. Faruqee, H., and Mühleisen, M. (2003). Population aging in Japan: demographic shock and fiscal sustainability. Japan and the World Economy, 15(2): 185-210. URL http://ideas.repec.org/a/eee/japwor/v15y2003i2p185-210.html.
50. Forbes, K., and Rigobon, R. (2002). No contagion, only interdependence: Measur- ing stock market comovements. Journal of Finance, 57(5): 2223-2261. URL http://web.mit.edu/kjforbes/www/Papers/NoContagion-JOF.pdf.
51. Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486(3-5): 75-174. URL http://arxiv.org/PS_cache/arxiv/pdf/0906/0906.0612v2.pdf.
52. Fox News (2010). Japan's prime minister survives leadership vote, now must revive sputtering economy. URL http://www.foxnews.com/world/2010/09/14/japan-pm-faces-powerful-challenger-leadership-vote-country-new-leader/.
53. Gilmore, C., Lucey, B., and Boscia, M. (2008). An ever-closer union? Examining the evolution of linkages of European equity markets via minimum spanning trees. Physica A, 387: 6319-6329.
54. Girvan, M., and Newman, M. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 99(12): 7821-7826. URL http://www.santafe.edu/media/workingpapers/01-12-077.pdf.
55. Gligor, M., and Ausloos, M. (2007). Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations. The European Physical Journal B, 57: 139-146. URL http://arxiv.org/abs/physics/0607098.
56. Goldfeld, S., and Quandt, R. (1973). A Markov model for switching regressions. Journal of Econometrics, 1(1): 3-15. URL http://ideas.repec.org/a/eee/econom/ v1y1973i1p3-15.html.
57. Gower, J., and Ross, G. (1969). Minimum spanning trees and single linkage cluster analysis. Journal of the Royal Statistical Society Series C, 18(1): 54-64. URL http://www.jstor.org/stable/2346439.
58. Guo, W., and Wohar, M. (2006). Identifying regime changes in market volatility. Journal of Financial Research, 29(1): 79-93. URL http://ideas.repec.org/a/bla/jfnres/v29y2006i1p79-93.html.
59. Hamilton, J. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2): 357-384. URL http://ideas.repec.org/a/ecm/emetrp/v57y1989i2p357-84.html.
60. Hansen, B. (2001). The new econometrics of structural change: Dating breaks in U.S. labor productivity. The Journal of Economic Perspectives, 15(4): 117-128. URL http://www.uibk.ac.at/econometrics/dl/jep01fall/09structchange.pdf.
61. Hayashi, F., and Prescott, E. (2002). The 1990s in Japan: A lost decade. Review of Economic Dynamics, 5(1): 206-235. URL http://ideas.repec.org/a/red/issued/v5y2002i1p206-235.html.
62. Hill, B. (1975). A simple general approach to inference about the tail of a distribu- tion. The Annals of Statistics, 3(5): 1163-1174. URL http://www.nslij-genetics.org/wli/zipf/hill75-as.pdf.
63. Hill, R. (1999). Comparing price levels across countries using minimum-spanning trees. The Review of Economics and Statistics, 81(1): 135-142. URL http://www.jstor.org/stable/2646792.
64. Hill, R. (2001). Measuring inflation and growth using spanning trees. International Economic Review, 42(1): 167-185. URL http://ideas.repec.org/a/ier/iecrev/v42y2001i1p167-85.html.
65. Hoshi, T., and Kashyap, A. (2004). Japan's financial crisis and economic stagnation. The Journal of Economic Perspectives, 18(1): 3-26. URL http://pzacad.pitzer.edu/~lyamane/hoshi1.pdf.
66. Iida, Y., and Matsumae, T. (2009). The dynamic effects of Japanese macroeconomic policies: Were there any changes in the 1990s? Economic and Social Research Institute. URL http://www.esri.go.jp/jp/archive/e_dis/e_dis210/e_dis209a.pdf.
67. Im, K.-S., Lee, J., and Tieslau, M. (2005). Panel LM unit-root tests with level shifts. Oxford Bulletin of Economics and Statistics, 67(3): 393-419. URL http://econpapers.repec.org/article/blaobuest/v_3a67_3ay_3a2005_3ai_3a3_3ap_3a393-419.htm.
68. Jacod, J., and Todorov, V. (2009). Testing for common arrivals of jumps for discretely observed multidimensional processes. Annals of Statistics, 37(4): 1792-1838. URL http://www.kellogg.northwestern.edu/faculty/todorov/htm/papers/jt.pdf.
69. Jain, A., Murty, M., and Flynn, P. (1999). Data clustering: A review. ACM Computing Surveys, 31(3): 264-323. URL http://doi.acm.org/10.1145/331499. 331504.
70. Japan Economy News & Blog (2010). IMF: Japan's national debt to hit 250% of GDP in 2015.
71. Johnson, S. (1967). Hierarchical clustering schemes. Psychometrika, 32(3): 241-254. URL http://ideas.repec.org/a/spr/psycho/v32y1967i3p241-254.html.
72. Jung, W.-S., Chae, S., Yang, J.-S., and Moon, H.-T. (2006). Characteristics of the Korean stock market correlations. Physica A, 361: 263-271. URL http://arxiv.org/abs/physics/0504009.
73. Jung, W.-S., Kwon, O., Wang, F., Kaizoji, T., Moon, H.-T., and Stanley, H. (2008). Group dynamics of the Japanese market. Physica A, 387: 537-542. URL http://ideas.repec.org/p/arx/papers/0708.0562.html.
74. Karolyi, G., and Stulz, R. (1996). Why do markets move together? An investigation of U.S.-Japan stock return comovements. Journal of Finance, 51(3): 951-986. URL http://ideas.repec.org/a/bla/jfinan/v51y1996i3p951-86.html.
75. Kim, C.-J., and Nelson, C. (1999). Has the U.S. economy become more stable? A Bayesian approach based on a Markov-switching model of business cycle. Review of Economics and Statistics, 81(4): 608-616. URL http://ideas.repec.org/a/tpr/restat/v81y1999i4p608-616.html.
76. Kim, D. (2009). Estimating a common deterministic time trend break in large panels with cross sectional dependence. Discussion paper, University of Virginia, Charlottesville. URL http://www.columbia.edu/~ao2027/Dukpa.pdf.Working paper.
77. Koutrouvelis, I. (1980). Regression-type estimation of the parameters of stable laws. Journal of the American Statistical Association, 75(372): 918-928. URL http://www.jstor.org/stable/2287182.
78. Koutrouvelis, I. A. (1981). An iterative procedure for the estimation of the parameters of stable laws. Communications in Statistics - Simulation and Com- putation, 10(1): 17-28. URL http://www.tandfonline.com/doi/abs/10.1080/03610918108812189.
79. Kruskal, J. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7(1): 48-50. URL http://www.jstor.org/stable/2033241.
80. Kulkarni, V., and Deo, N. (2007). Correlation and volatility in an Indian stock market: A random matrix approach. The European Physical Journal B, 60: 101-109. URL http://www.springerlink.com/content/38m04076514r4051/.
81. Kurihara, J. (2007). Demystifying Japan's Economic Recovery. Business Economics, 42(3): 29-35. URL http://econpapers.repec.org/article/palbuseco/v_3a42_3ay_3a2007_3ai_3a3_3ap_3a29-35.htm.
82. Laloux, L., Cizeau, P., Bouchaud, J.-P., and Potters, M. (1999). Noise dressing of financial correlation matrices. Physical Review Letters, 83(7): 1467-1470. URL http://arxiv.org/abs/cond-mat/9810255.
83. Lancichinetti, A., and Fortunato, S. (2009). Community detection algorithms: A comparative analysis. Physical Review E, 80(5): 056117. URL http://arxiv.org/abs/0908.1062.
84. Lavielle, M., and Moulines, E. (2000). Least-squares estimation of an unknown number of shifts in a time series. Journal of Time Series Analysis, 21(1): 33-59. URL http://onlinelibrary.wiley.com/doi/10.1111/1467-9892.00172/pdf.
85. Lee, G., Zhang, Y., Wong, J., Prusty, M., and Cheong, S. (25 Nov 2009). Causal links in US economic sectors. URL http://arxiv.org/abs/0911.4763.ArXiv:0911.4763.
86. Li, W. (2001a). DNA segmentation as a model selection process. In Proceedings of the International Conference on Research in Computational Molecular Biology (RECOMB), pages 204-210. URL http://arxiv.org/abs/physics/0104026.
87. Li, W. (2001b). New stopping criteria for segmenting DNA sequences. Physical Review Letters, 86(25): 5815-5818. URL http://arxiv.org/abs/physics/0104027.
88. Lin, J. (1991). Divergence measures based on the Shannon entropy. IEEE Transactions on Information Theory, 37(1): 145-151. URL http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=61115&userType=inst.
89. Lo, A. (2009). Regulatory reform in the wake of the financial crisis of 2007-2008. Journal of Financial Economic Policy, 1(1): 4-43. URL http://ideas.repec.org/aeme/jfeppp/v1y2009i1p4-43.html.
90. Loader, C. (1996). Change point estimation using nonparametric regression. Annals of Statistics, 24(4): 1667-1678. URL http://www.jstor.org/stable/2242744.
91. Lumsdaine, R., and Papell, D. (1997). Multiple trend breaks and the unit-root hypothesis. Review of Economics and Statistics, 79(2): 212-218. URL http://www.jstor.org/stable/2951453.
92. MacKellar, L. (2004). Economic impacts of population aging in Japan. Cheltenham: Edward Elgar Publishing.
93. Mantegna, R. (1999). Hierarchical structure in financial markets. The European Physical Journal B, 11: 193-197. URL http://arxiv.org/abs/cond-mat/9802256.
94. Mantegna, R., and Stanley, H. (1995). Scaling behaviour in the dynamics of an economic index. Nature, 376: 46-49. URL http://www.nature.com/nature/journal/v376/n6535/abs/376046a0.html.
95. Matteo, T. D., and Aste, T. (12 Dec 2005). Extracting the correlation structure by means of planar embedding. In Proceedings of the SPIE Conference on Complex Systems, volume 6039, pages 227-236. URL http://people.physics.anu.edu.au/~tdm110/Articoli_web/My%20articles/2006/SPIEDiMatteo_1.pdf.
96. McCulloch, J. (1986). Simple consistent estimators of stable distribution parameters. Communications in Statistics - Simulation and Computation, 15(4): 1109-1136. URL http://dx.doi.org/10.1080/03610918608812563.
97. McCulloch, J., and Panton, D. (1997). Precise tabulation of the maximally-skewed stable distributions and densities. Computational Statistics & Data Analysis, 23(3): 307-320. URL http://ideas.repec.org/a/eee/csdana/v23y1997i3p307-320.html.
98. Miccichè, S., Bonanno, G., Lillo, F., and Mantegna, R. (2003). Degree stability of a minimum spanning tree of price return and volatility. Physica A, 324: 66-73. URL http://econpapers.repec.org/paper/arxpapers/cond-mat_2f0212338.htm.
99. Miskiewicz, J., and Ausloos, M. (2006). An attempt to observe economy globalization: The cross correlation distance evolution of the top 19 GDPs. International Journal of Modern Physics C, 17(3): 317-331. URL http://arxiv.org/abs/physics/0509165.
100. Münnix, M., Schäfer, R., and Grothe, O. (30 Jun 2010). Estimating correlation and covariance matrices by weighting of market similarity. URL http://arxiv.org/abs/1006.5847.ArXiv:1006.5847.
101. Newman, M. (2004). Detecting community structure in networks. The European Physical Journal B, 38(2): 321-330. URL http://www-personal.umich.edu/~mejn/papers/epjb.pdf.
102. Newman, M. (2006). Modularity and community structure in networks. Pro- ceedings of the National Academy of Sciences of the United States of America, 103(23): 8577-8582. URL http://www.mendeley.com/research/modularity-community-structure-networks-56/.
103. Nolan, J. (1997). Numerical calculation of stable densities and distribution functions. Stochastic Models, 13(4): 759-774.
104. Nolan, J. (1998). Parameterizations and modes of stable distributions. Statistics & Probability Letters, 38(2): 187-195. URL http://ideas.repec.org/a/eee/stapro/v38y1998i2p187-195.html.
105. Nolan, J. (1999). An algorithm for evaluating stable densities in Zolotarev's (M) parameterization. Mathematical and Computer Modelling, 29(10-12): 229-233. URL http://www.sciencedirect.com/science/article/pii/S0895717799001053.
106. Nolan, J. (2001). Maximum likelihood estimation and diagnostics for stable distributions Lévy Processes Theory and Applications. In T. M. O.E. Barndorff-Nielsen, and S. Resnick (Eds.), Lévy Processes Theory and Applications, pages 379-400. Boston: Birkhäuser. URL http://academic2.american.edu/~jpnolan/stable/mle.pdf. O. E. Barndorff-Nielsen and T. Mikosch and S. I. Resnick.
107. Onnela, J.-P., Chakraborti, A., Kaski, K., and Kertész, J. (2003a). Dynamic asset trees and Black Monday. Physica A, 324: 247-252. URL http://arxiv.org/abs/cond-mat/0212037.
108. Onnela, J.-P., Chakraborti, A., Kaski, K., Kertész, J., and Kanto, A. (2003b). Asset trees and asset graphs in financial markets. Physica Scripta, T106: 48-54. URL http://lib.tkk.fi/Diss/2006/isbn9512282704/article3.pdf.
109. Onnela, J.-P., Chakraborti, A., Kaski, K., Kertész, J., and Kanto, A. (2003c). Dynamics of market correlations: Taxonomy and portfolio analysis. Physical Review E, 68(5): 056110. URL http://lib.tkk.fi/Diss/2006/isbn9512282704/article4.pdf.
110. Onnela, J.-P., Kaski, K., and Kertész, J. (2004). Clustering and information in correlation based financial networks. The European Physical Journal B, 38: 353-362. URL http://lib.tkk.fi/Diss/2006/isbn9512282704/article5.pdf.
111. Panton, D. (1992). Cumulative distribution function values for symmetric standardized stable distributions. Communications in Statistics - Simulation and Computation, 21(2): 485-492.
112. Panton, D. B., Lessig, V. P., and Joy, O. M. (1976). Comovement of inter- national equity markets: A taxonomic approach. Journal of Financial and Quantitative Analysis, 11(3): 415-432. URL http://ideas.repec.org/a/cup/jfinqa/v11y1976i03p415-432_02.html.
113. Perron, P., and Zhu, X. (2005). Structural breaks with deterministic and stochastic trends. Journal of Econometrics, 129(1-2): 65-119. URL http://ideas.repec.org/a/eee/econom/v129y2005i1-2p65-119.html.
114. Plerou, V., Gopikrishnan, P., Rosenow, B., Amaral, L., Guhr, T., and Stanley, H. (2002). Random matrix approach to cross correlations in financial data. Physical Review E, 65(6): 066126. URL http://polymer.bu.edu/hes/articles/pgrags02.pdf.
115. Posen, A. (1998). Restoring Japan's economic growth. Washington, DC: Petersen Institute.
116. Reichardt, J., and Bornholdt, S. (2006). Statistical mechanics of community detection. Physical Review E, 74(1): 016110. URL http://pre.aps.org/abstract/PRE/v74/i1/e016110.
117. Reuters (2010). IMF urges tax increase to tackle Japan debt. URL http://www.reuters.com/article/2010/07/14/imf-japan-idUSNLLEIE69620100714.
118. Rigobon, R. (2003). On the measurement of the international propagation of shocks: Is the transmission stable? Journal of International Economics, 61(2): 261-283. URL http://ideas.repec.org/a/eee/inecon/v61y2003i2p261-283.html.
119. Román-Roldán, R., Bernaola-Galván, P., and Oliver, J. (1998). Sequence compositional complexity of DNA through an entropic segmentation method. Physical Review Letters, 80(6): 1344-1347. URL http://www.nslij-genetics.org/dnacorr/roman98.pdf.
120. Shen, J., and Zheng, B. (2009). Cross-correlation in financial dynamics. Euro-physics Letters, 86: 1-6. URL http://iopscience.iop.org/0295-5075/86/4/48005.
121. Sneath, P. H. A. (1957). The application of computers to taxonomy. Journal of General Microbiology, 17: 201-226. URL http://www.ncbi.nlm.nih.gov/pubmed/13475686.
122. Stockman, A., and Tesar, L. (1995). Tastes and technology in a two-country model of the business cycle: Explaining international comovement. The American Economic Review, 85(1): 168-185. URL http://ideas.repec.org/a/aea/aecrev/v85y1995i1p168-85.html.
123. Today (2011). New faces to revive Japan's economy. URL http://www.todayonline.com/World/EDC110115-0000209/New-faces-to-revive-Japans-economy.
124. Tóth, B., Lillo, F., and Farmer, J. (2010). Segmentation algorithm for non-stationary compound Poisson processes. The European Physical Journal B - Condensed Matter and Complex Systems, 78(2): 235-243. URL http://tuvalu.santafe.edu/~jdf/papers/SegmentationAlgorithm.pdf.
125. Tudor, C. (2009). Understanding the roots of the US Subprime Crisis and its subsequent effects. The Romanian Economic Journal, 31: 115-148. URL http://www.rejournal.eu/Portals/0/Arhiva/JE%2031/JE%2031%20-%20Cristiana%20TUDOR.pdf.
126. Tumminello, M., Matteo, T. D., Aste, T., and Mantegna, R. (2007). Correlation based networks of equity returns sampled at different time horizons. The European Physical Journal B, 55: 209-217. URL http://people.physics.anu.edu.au/~tas110/Pubblicazioni/EPJB_CorrReturn07.pdf.
127. Utsugi, A., Ino, K., and Oshikawa, M. (2004). Random matrix theory analysis of cross correlations in financial markets. Physical Review E, 70(2): 026110. URL http://arxiv.org/abs/cond-mat/0312643.
128. Vaglica, G., Lillo, F., Moro, E., and Mantegna, R. (2008). Scaling laws of strategic behavior and size heterogeneity in agent dynamics. Physical Review E, 77(3): 1-6. URL http://pre.aps.org/abstract/PRE/v77/i3/e036110.
129. Wall Street Journal (2009). Japanese reform gets lost in the mail. URL http://online.wsj.com/article/SB10001424052748703363704574502651479212142.html.
130. Wilcox, D., and Gebbie, T. (2004). On the analysis of cross-correlations in South African market data. Physica A, 344: 294-298. URL http://www.sciencedirect.com/science/article/pii/S0378437104009537.
131. Wilcox, D., and Gebbie, T. (2007). An analysis of cross-correlations in an emerging market. Physica A, 375: 584-598.
132. Wong, D., and Li, K.-W. (2010). Comparing the performance of relative stock return differential and real exchange rate in two financial crises. Applied Fi- nancial Economics, 20(1): 137-150. URL http://ideas.repec.org/a/taf/apfiec/v20y2010i1-2p137-150.html.
133. Wong, J., Lian, H., and Cheong, S. (2009). Detecting macroeconomic phases in the Dow Jones Industrial Average time series. Physica A, 388(21): 4635-4645. URL http://dr.ntu.edu.sg/handle/10220/6107.
134. Worsdale, G. (1975). Tables of cumulative distribution functions for symmetric stable distributions. Journal of the Royal Statistical Society Series C (Applied Statistics), 24(1): 123-131. URL http://www.jstor.org/stable/2346710.
135. Yim, W. (Nov 2010). Between Japanese economic sectors. Master's thesis, Nanyang Technological University.
136. Yoshino, N., and Mizoguchi, T. (2010). The role of public works in the political business cycle and the instability of the budget deficits in Japan. Asian Economic Papers, 9(1): 94-112. URL http://econpapers.repec.org/article/tprasiaec/v_3a9_3ay_3a2010_3ai_3a1_3ap_3a94-112.htm.
137. Zhang, Y., Lee, G., Wong, J., Kok, J., Prusty, M., and Cheong, S. (2011). Will the US economy recover in 2010? A minimal spanning tree study. Physica A, 390(11): 2020-2050. URL http://www.sciencedirect.com/science/article/pii/S0378437111000847.
138. Zivot, E., and Andrews, D. (2002). Further evidence on the Great Crash, the oil-price shock, and the unit-root hypothesis. Journal of Business and Economic Statistics, 20(1): 25-44. URL http://ideas.repec.org/a/bes/jnlbes/v20y2002i1p25-44.html.
139. Zolotarev, V. (1986). One-dimensional stable distributions. Providence: American Mathematical Society.