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Blockchain mechanism and distributional characteristics of cryptos
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22
Appendix
Table 1: Characteristics of prices of di erent cryptocurrencies
Characteristic Bitcoin Ethereum LitecoinBitcoin
CashEthereum
ClassicXRP
mean 2659.127 178.966 34.394 537.723 9.381 0.192
standard deviation 3798.466 222.452 48.645 509.244 7.827 0.302
skewness 1.338 1.950 2.389 2.322 1.491 4.193
kurtosis 0.672 4.654 7.272 6.157 2.239 29.471
maximum 19401.000 1356.000 352.799 3526.000 43.765 3.649
minimum 0.050 0.401 0.032 58.626 0.687 0.003
lowerquant 20.193 7.975 3.153 233.404 4.364 0.007
median 455.892 136.557 8.618 324.646 6.571 0.024
upperquant 5128.000 250.965 53.128 620.947 13.813 0.291
VaR99 0.062 0.578 0.040 107.426 0.809 0.004
VaR95 0.393 0.696 0.072 129.491 1.105 0.005
slope 2.781 0.163 0.032 -0.876 -0.002 0.000
intercept 0.050 2.820 0.033 63.765 0.892 0.006
autocorrelation 0.998 0.998 0.997 0.992 0.994 0.991
selfsimilarity 1.574 1.611 1.596 1.609 1.564 1.551
chaos 0.088 0.093 0.091 0.086 0.087 0.085
CharacteristicBitcoin
SVDash Zcash Monero DogecoinBitcoin
Gold
mean 145.401 113.910 135.596 57.588 0.006 43.167
standard deviation 66.784 187.915 125.654 75.569 0.193 70.420
skewness 0.678 3.126 1.756 2.145 49.692 2.879
kurtosis 0.079 11.777 3.208 5.300 2469.511 8.351
maximum 370.647 1436.000 728.159 439.391 9.608 513.293
minimum 52.683 0.516 23.940 0.233 0.000 5.093
lowerquant 87.323 3.950 50.251 1.100 0.000 9.710
median 135.217 66.508 72.251 44.090 0.001 15.869
upperquant 191.739 133.239 199.807 84.834 0.003 29.706
VaR99 53.377 0.711 27.767 0.272 0.000 5.357
VaR95 62.111 1.833 31.842 0.417 0.000 6.604
slope 0.218 0.083 -0.134 0.053 0.000 -0.147
intercept 111.700 1.380 286.297 1.911 0.000 513.293
autocorrelation 0.990 0.997 0.995 0.997 0.002 0.961
selfsimilarity 1.628 1.642 1.573 1.577 1.024 1.431
chaos 0.077 0.090 0.092 0.091 0.086 0.073
CharacteristicPeer
coinVertcoinRedd-
coinFeather-
coinBlack-
coinNova-
coin
mean 1.004 0.670 0.001 0.062 0.095 2.185
standard deviation 1.238 1.319 0.003 0.102 0.127 2.989
skewness 2.511 3.637 4.175 3.379 3.397 3.102
kurtosis 7.017 14.792 24.526 17.172 15.251 12.916
maximum 9.118 9.386 0.029 1.203 1.108 24.777
minimum 0.110 0.006 0.000 0.002 0.014 0.078
lowerquant 0.291 0.043 0.000 0.008 0.030 0.507
median 0.445 0.237 0.001 0.019 0.045 0.901
upperquant 1.275 0.626 0.001 0.072 0.088 3.301
VaR99 0.125 0.009 0.000 0.003 0.015 0.156
VaR95 0.168 0.015 0.000 0.004 0.020 0.187
slope 0.000 0.000 0.000 0.000 0.000 -0.001
intercept 0.382 6.315 0.000 0.559 0.035 0.078
autocorrelation 0.993 0.992 0.988 0.983 0.993 0.994
selfsimilarity 1.577 1.603 1.548 1.523 1.537 1.596
chaos 0.088 0.085 0.079 0.078 0.084 0.09123
Table 2: Characteristics of Block time of di erent cryptocurrencies
Characteristic Bitcoin Ethereum LitecoinBitcoin
CashEthereum
ClassicXRP
mean 10.453 0.257 2.507 11.167 0.246 NA
standard deviation 8.814 0.045 0.385 11.009 0.032 NA
skewness 21.779 3.098 5.003 11.597 5.144 NA
kurtosis 701.717 11.987 54.589 160.209 61.066 NA
maximum 360.000 0.509 8.521 205.714 0.800 NA
minimum 2.081 0.208 0.149 1.275 0.153 NA
lowerquant 8.623 0.235 2.357 9.664 0.235 NA
median 9.474 0.241 2.474 9.931 0.238 NA
upperquant 10.435 0.268 2.599 10.360 0.242 NA
VaR99 5.923 0.220 1.710 2.331 0.215 NA
VaR95 7.129 0.222 2.111 8.479 0.218 NA
slope -0.001 0.000 0.000 -0.007 0.000 NA
intercept 102.857 0.208 0.149 160.000 0.208 NA
autocorrelation 0.494 0.981 0.705 0.395 0.818 NA
selfsimilarity 1.027 1.522 0.787 0.704 1.249 NA
chaos 0.012 0.070 0.012 0.003 0.068 NA
CharacteristicBitcoin
SVDash Zcash Monero DogecoinBitcoin
Gold
mean 10.195 2.659 2.409 1.686 1.048 9.823
standard deviation 1.639 0.805 0.345 0.541 0.043 0.741
skewness 12.504 19.831 -3.025 3.258 -9.220 -5.375
kurtosis 221.950 409.827 7.261 57.807 222.460 60.686
maximum 40.000 22.500 2.618 10.992 1.288 11.250
minimum 7.310 0.348 1.240 0.829 0.100 0.254
lowerquant 9.600 2.609 2.487 1.025 1.038 9.664
median 10.000 2.623 2.509 1.951 1.044 9.931
upperquant 10.511 2.637 2.531 2.020 1.050 10.141
VaR99 8.361 2.476 1.248 0.947 0.980 7.767
VaR95 9.034 2.571 1.258 0.984 1.031 8.623
slope -0.001 0.000 0.000 0.001 0.000 0.001
intercept 40.000 0.348 2.286 1.627 0.100 0.254
autocorrelation -0.115 0.707 0.982 0.805 0.787 0.378
selfsimilarity 0.367 0.811 1.121 0.922 1.044 0.494
chaos 0.023 0.003 0.010 0.001 0.011 -0.001
CharacteristicPeer-
coinVert-
coinRedd-
coinFeather-
coinBlack-
coinNova-
coin
mean 10.085 2.502 4.646 2.005 1.090 6.819
standard deviation 47.070 0.180 68.175 6.443 0.105 2.295
skewness 30.324 -1.782 20.761 11.521 -4.368 24.326
kurtosis 919.356 30.015 434.280 157.793 18.525 891.281
maximum 1440.000 4.079 1440.000 130.909 1.335 96.000
minimum 1.377 0.151 0.646 0.148 0.442 0.451
lowerquant 7.742 2.412 0.986 1.042 1.111 6.154
median 8.372 2.500 1.007 1.048 1.114 6.606
upperquant 9.057 2.590 1.028 1.171 1.117 7.164
VaR99 5.464 2.144 0.935 1.034 0.551 4.364
VaR95 6.545 2.289 0.957 1.036 0.949 5.390
slope -0.003 0.000 -0.010 -0.002 0.000 -0.001
intercept 1440.000 0.151 1440.000 0.291 1.309 1.765
autocorrelation 0.667 0.154 0.821 0.914 0.976 0.373
selfsimilarity 0.717 0.437 1.051 1.210 1.337 0.697
chaos 0.002 0.008 -0.001 0.032 0.006 0.00924
Table 3: Characteristics of Block size of di erent cryptocurrencies
Characteristic Bitcoin Ethereum LitecoinBitcoin
CashEthereum
ClassicXRP
mean 407162.152 14376.916 12909.684 138173.724 1297.638 NA
standard deviation 363245.372 11337.562 15590.195 284058.956 340.581 NA
skewness 0.241 0.285 4.309 9.176 0.679 NA
kurtosis -1.583 -0.819 31.780 109.791 2.106 NA
maximum 998092.000 58953.000 206020.000 4710539.000 3594.000 NA
minimum 134.000 575.164 134.000 4982.000 575.164 NA
lowerquant 21246.000 1627.750 4004.750 60455.500 1054.750 NA
median 310990.000 17024.000 7016.000 94775.000 1310.500 NA
upperquant 777369.500 23068.750 19366.500 122827.500 1492.250 NA
VaR99 134.548 658.423 561.630 15574.520 653.404 NA
VaR95 134.952 788.678 800.306 27169.700 775.052 NA
slope 266.541 17.464 8.806 -89.253 0.189 NA
intercept 204.000 643.886 199.000 385996.000 643.886 NA
autocorrelation 0.985 0.981 0.872 0.626 0.850 NA
selfsimilarity 1.067 1.310 1.148 1.074 1.131 NA
chaos 0.058 0.058 0.065 0.027 0.045 NA
CharacteristicBitcoin
SVDash Zcash Monero DogecoinBitcoin
Gold
mean 1100149.254 12999.389 23802.102 39874.397 10523.242 25312.953
standard deviation 1278250.457 26340.294 38911.209 47310.430 6607.125 67527.275
skewness 6.673 27.654 8.711 1.703 5.917 6.269
kurtosis 84.455 1040.743 117.847 4.063 68.981 45.828
maximum 20460199.000 1059232.000 687685.000 347816.000 116605.000 739259.000
minimum 5005.000 226.545 379.573 375.434 143.000 133.000
lowerquant 257789.500 3038.000 7189.500 3047.250 6775.000 6512.500
median 996071.500 9240.000 11670.000 20980.000 9510.000 9316.000
upperquant 1573243.000 19193.000 28242.000 62002.000 12022.000 14118.000
VaR99 6435.000 1312.960 2605.530 1058.990 3432.400 2727.870
VaR95 14660.750 1736.200 3103.900 1320.350 4491.000 3983.600
slope 2318.003 14.357 -25.267 26.939 1.018 -67.625
intercept 10871172.000 226.545 379.573 375.434 143.000 133.000
autocorrelation 0.377 0.298 0.836 0.958 0.798 0.618
selfsimilarity 1.004 0.947 1.138 1.214 1.070 1.015
chaos 0.009 0.018 0.030 0.041 0.021 -0.012
CharacteristicPeer-
coinVert-
coinRedd-
coinFeather-
coinBlack-
coinNova-
coin
mean NA 2641.881 772.025 806.556 687.622 539.712
standard deviation NA 3611.409 634.442 1621.154 3441.373 1223.175
skewness NA 3.420 3.613 10.605 28.388 38.218
kurtosis NA 16.189 21.857 158.924 894.526 1712.453
maximum NA 36709.000 7808.000 36789.000 120169.000 57527.000
minimum NA 105.000 105.000 109.625 252.514 110.835
lowerquant NA 682.104 388.361 359.746 286.296 360.352
median NA 1149.000 526.043 460.827 386.251 436.181
upperquant NA 3185.000 937.696 598.841 627.727 542.228
VaR99 NA 248.950 317.797 126.333 255.520 262.588
VaR95 NA 310.697 337.320 247.907 261.297 284.524
slope NA -0.586 -0.475 -0.739 -0.025 -0.204
intercept NA 130.000 175.000 109.625 464.500 141.000
autocorrelation NA 0.894 0.609 0.705 0.360 0.069
selfsimilarity NA 1.129 1.007 1.063 0.959 0.951
chaos NA 0.100 0.034 0.034 0.039 0.01125
IRTG 1792 Discussion Paper Series 2020
For a complete list of Discussion Papers published, please visit
http://irtg1792.hu-berlin.de.
|
2011.13240#403
|
2011.13240#405
|
2011.13240
|
2011.13240#405
|
Blockchain mechanism and distributional characteristics of cryptos
|
001 ”Estimation and Determinants of Chinese Banks’ Total Factor Efficiency: A New
Vision Based on Unbalanced Development of Chinese Banks and Their Overall Risk”
by Shiyi Chen, Wolfgang K.
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2011.13240#404
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2011.13240#406
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2011.13240
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2011.13240#406
|
Blockchain mechanism and distributional characteristics of cryptos
|
H¨ ardle, Li Wang, January 2020.
|
2011.13240#405
|
2011.13240#407
|
2011.13240
|
2011.13240#407
|
Blockchain mechanism and distributional characteristics of cryptos
|
002 ”Service Data Analytics and Business Intelligence” by Desheng Dang Wu, Wolfgang
Karl H¨ ardle, January 2020.
|
2011.13240#406
|
2011.13240#408
|
2011.13240
|
2011.13240#408
|
Blockchain mechanism and distributional characteristics of cryptos
|
003 ”Structured climate financing: valuation of CDOs on inhomogeneous asset pools”
by Natalie Packham, February 2020.
|
2011.13240#407
|
2011.13240#409
|
2011.13240
|
2011.13240#409
|
Blockchain mechanism and distributional characteristics of cryptos
|
004 ”Factorisable Multitask Quantile Regression” by Shih-Kang Chao, Wolfgang K.
|
2011.13240#408
|
2011.13240#410
|
2011.13240
|
2011.13240#410
|
Blockchain mechanism and distributional characteristics of cryptos
|
H¨ ardle, Ming Yuan, February 2020.
|
2011.13240#409
|
2011.13240#411
|
2011.13240
|
2011.13240#411
|
Blockchain mechanism and distributional characteristics of cryptos
|
005 ”Targeting Cutsomers Under Response-Dependent Costs” by Johannes Haupt, Ste-
fan Lessmann, March 2020.
|
2011.13240#410
|
2011.13240#412
|
2011.13240
|
2011.13240#412
|
Blockchain mechanism and distributional characteristics of cryptos
|
006 ”Forex exchange rate forecasting using deep recurrent neural networks” by Alexander
Jakob Dautel, Wolfgang Karl H¨ ardle, Stefan Lessmann, Hsin-Vonn Seow, March
2020.
|
2011.13240#411
|
2011.13240#413
|
2011.13240
|
2011.13240#413
|
Blockchain mechanism and distributional characteristics of cryptos
|
007 ”Deep Learning application for fraud detection in financial statements” by Patricia
Craja, Alisa Kim, Stefan Lessmann, May 2020.
|
2011.13240#412
|
2011.13240#414
|
2011.13240
|
2011.13240#414
|
Blockchain mechanism and distributional characteristics of cryptos
|
008 ”Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown
Function” by Kun Ho Kim, Shih-Kang Chao, Wolfgang K.
|
2011.13240#413
|
2011.13240#415
|
2011.13240
|
2011.13240#415
|
Blockchain mechanism and distributional characteristics of cryptos
|
H¨ ardle, May 2020.
|
2011.13240#414
|
2011.13240#416
|
2011.13240
|
2011.13240#416
|
Blockchain mechanism and distributional characteristics of cryptos
|
009 ”CRIX an Index for cryptocurrencies” by Simon Trimborn, Wolfgang Karl H¨ ardle,
May 2020. 010 ”Kernel Estimation: the Equivalent Spline Smoothing Method” by Wolfgang K.
|
2011.13240#415
|
2011.13240#417
|
2011.13240
|
2011.13240#417
|
Blockchain mechanism and distributional characteristics of cryptos
|
H¨ ardle, Michael Nussbaum, May 2020.
|
2011.13240#416
|
2011.13240#418
|
2011.13240
|
2011.13240#418
|
Blockchain mechanism and distributional characteristics of cryptos
|
011 ”The Effect of Control Measures on COVID-19 Transmission and Work Resumption:
International Evidence” by Lina Meng, Yinggang Zhou, Ruige Zhang, Zhen Ye,
Senmao Xia, Giovanni Cerulli, Carter Casady, Wolfgang K.
|
2011.13240#417
|
2011.13240#419
|
2011.13240
|
2011.13240#419
|
Blockchain mechanism and distributional characteristics of cryptos
|
H¨ ardle, May 2020.
|
2011.13240#418
|
2011.13240#420
|
2011.13240
|
2011.13240#420
|
Blockchain mechanism and distributional characteristics of cryptos
|
012 ”On Cointegration and Cryptocurrency Dynamics” by Georg Keilbar, Yanfen Zhang,
May 2020.
|
2011.13240#419
|
2011.13240#421
|
2011.13240
|
2011.13240#421
|
Blockchain mechanism and distributional characteristics of cryptos
|
013 ”A Machine Learning Based Regulatory Risk Index for Cryptocurrencies” by Xinwen
Ni, Wolfgang Karl H¨ ardle, Taojun Xie, August 2020.
|
2011.13240#420
|
2011.13240#422
|
2011.13240
|
2011.13240#422
|
Blockchain mechanism and distributional characteristics of cryptos
|
014 ”Cross-Fitting and Averaging for Machine Learning Estimation of Heterogeneous
Treatment Effects” by Daniel Jacob, August 2020.
|
2011.13240#421
|
2011.13240#423
|
2011.13240
|
2011.13240#423
|
Blockchain mechanism and distributional characteristics of cryptos
|
015 ”Tail-risk protection: Machine Learning meets modern Econometrics” by Bruno
Spilak, Wolfgang Karl H¨ ardle, October 2020.
|
2011.13240#422
|
2011.13240#424
|
2011.13240
|
2011.13240#424
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Blockchain mechanism and distributional characteristics of cryptos
|
016 ”A data-driven P-spline smoother and the P-Spline-GARCH models” by Yuanhua
Feng, Wolfgang Karl H¨ ardle, October 2020.
|
2011.13240#423
|
2011.13240#425
|
2011.13240
|
2011.13240#425
|
Blockchain mechanism and distributional characteristics of cryptos
|
017 ”Using generalized estimating equations to estimate nonlinear models with spatial
data” by Cuicui Lu, Weining Wang, Jeffrey M.
|
2011.13240#424
|
2011.13240#426
|
2011.13240
|
2011.13240#426
|
Blockchain mechanism and distributional characteristics of cryptos
|
Wooldridge, October 2020.
|
2011.13240#425
|
2011.13240#427
|
2011.13240
|
2011.13240#427
|
Blockchain mechanism and distributional characteristics of cryptos
|
018 ”A supreme test for periodic explosive GARCH” by Stefan Richter, Weining Wang,
Wei Biao Wu, October 2020.
|
2011.13240#426
|
2011.13240#428
|
2011.13240
|
2011.13240#428
|
Blockchain mechanism and distributional characteristics of cryptos
|
019 ”Inference of breakpoints in high-dimensional time series” by Likai Chen, Weining
Wang, Wei Biao Wu, October 2020.
|
2011.13240#427
|
2011.13240#429
|
2011.13240
|
2011.13240#429
|
Blockchain mechanism and distributional characteristics of cryptos
|
IRTG 1792, Spandauer Strasse 1, D-10178 Berlin
http://irtg1792.hu-berlin.de
This research was supported by the Deutsche
Forschungsgemeinschaft through the IRTG 1792.
|
2011.13240#428
|
2011.13240#430
|
2011.13240
|
2011.13240#430
|
Blockchain mechanism and distributional characteristics of cryptos
|
IRTG 1792 Discussion Paper Series 2020
For a complete list of Discussion Papers published, please visit
http://irtg1792.hu-berlin.de.
|
2011.13240#429
|
2011.13240#431
|
2011.13240
|
2011.13240#431
|
Blockchain mechanism and distributional characteristics of cryptos
|
020 ”Long- and Short-Run Components of Factor Betas: Implications for Stock Pricing”
by Hossein Asgharian, Charlotte Christiansen, Ai Jun Hou, Weining Wang, October
2020.
|
2011.13240#430
|
2011.13240#432
|
2011.13240
|
2011.13240#432
|
Blockchain mechanism and distributional characteristics of cryptos
|
021 ”Improved Estimation of Dynamic Models of Conditional Means and Variances” by
Weining Wang, Jeffrey M.
|
2011.13240#431
|
2011.13240#433
|
2011.13240
|
2011.13240#433
|
Blockchain mechanism and distributional characteristics of cryptos
|
Wooldridge, Mengshan Xu, October 2020.
|
2011.13240#432
|
2011.13240#434
|
2011.13240
|
2011.13240#434
|
Blockchain mechanism and distributional characteristics of cryptos
|
022 ”Tail Event Driven Factor Augmented Dynamic Model” by Weining Wang, Lining
Yu, Bingling Wang, October 2020.
|
2011.13240#433
|
2011.13240#435
|
2011.13240
|
2011.13240#435
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Blockchain mechanism and distributional characteristics of cryptos
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023 ”The common and speci
fic components of infl ation expectation across European countries” by Shi Chen,
Wolfgang Karl H¨ ardle, Weining Wang, October 2020.
|
2011.13240#434
|
2011.13240#436
|
2011.13240
|
2011.13240#436
|
Blockchain mechanism and distributional characteristics of cryptos
|
024 ”Dynamic Spatial Network Quantile Autoregression” by Xiu Xu, Weining Wang,
Yongcheol Shin, October 2020.
|
2011.13240#435
|
2011.13240#437
|
2011.13240
|
2011.13240#437
|
Blockchain mechanism and distributional characteristics of cryptos
|
025 ”Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data”
by Konul Mustafayeva, Weining Wang, October 2020.
|
2011.13240#436
|
2011.13240#438
|
2011.13240
|
2011.13240#438
|
Blockchain mechanism and distributional characteristics of cryptos
|
026 ”Data Analytics Driven Controlling: bridging statistical modeling and managerial
intuition” by Kainat Khowaja, Danial Saef, Sergej Sizov, Wolfgang Karl H¨ ardle,
November 2020.
|
2011.13240#437
|
2011.13240#439
|
2011.13240
|
2011.13240#439
|
Blockchain mechanism and distributional characteristics of cryptos
|
027 ”Blockchain mechanism and distributional characteristics of cryptos” by Min-Bin
Lin, Kainat Khowaja, Cathy Yi-Hsuan Chen, Wolfgang Karl H¨ ardle, November 2020.
|
2011.13240#438
|
2011.13240#440
|
2011.13240
|
2011.13240#440
|
Blockchain mechanism and distributional characteristics of cryptos
|
IRTG 1792, Spandauer Strasse 1, D-10178 Berlin
http://irtg1792.hu-berlin.de
This research was supported by the Deutsche
Forschungsgemeinschaft through the IRTG 1792.
|
2011.13240#439
|
2011.13240
|
|
2301.02734#0
|
Political, economic, and governance attitudes of blockchain users
|
Political, economic, and governance attitudes of blockchain users
Lucia M. Korpas
1
, Seth Fr ey
2,3
, Joshua Tan
1,4*
1
The Metagovernance Project, Brookline, MA, USA
2
Department of Communication, University of California
Davis, Davis, CA, USA
3
The Ostrom Workshop, Indiana University , Bloomington,
IN, USA
4
University of Oxford, Oxford, Oxfordshire, UK
* Corr espondence:
Joshua Tan
joshua.z.tan@gmail.com
Abstract
We
present
a
survey
to
evaluate
crypto-political,
crypto-economic,
and
crypto-governance
sentiment
in
people
who
are
part
of
a
blockchain
ecosystem.
|
2301.02734#1
|
2301.02734
|
|
2301.02734#1
|
Political, economic, and governance attitudes of blockchain users
|
Based
on
3710
survey
responses,
we
describe
their
beliefs,
attitudes,
and
modes
of
participation
in
crypto
and
investigate
how
self-reported
political
affiliation
and
blockchain
ecosystem
affiliation
are
associated
with
these.
|
2301.02734#0
|
2301.02734#2
|
2301.02734
|
2301.02734#2
|
Political, economic, and governance attitudes of blockchain users
|
We
observed
polarization
in
questions
on
perceptions
of
the
distribution
of
economic
power ,
personal
attitudes
towards
crypto,
normative
beliefs
about
the
distribution
of
power
in
governance,
and
external
regulation
of
blockchain
technologies.
|
2301.02734#1
|
2301.02734#3
|
2301.02734
|
2301.02734#3
|
Political, economic, and governance attitudes of blockchain users
|
Differences
in
political
self-identification
correlated
with
opinions
on
economic
fairness,
gender
equity ,
decision-making
power
and
how
to
obtain
favorable
regulation,
while
blockchain
affiliation
correlated
with
opinions
on
governance
and
regulation
of
crypto
and
respondents’
semantic
conception
of
crypto
and
personal
goals
for
their
involvement.
|
2301.02734#2
|
2301.02734#4
|
2301.02734
|
2301.02734#4
|
Political, economic, and governance attitudes of blockchain users
|
We
also
find
that
a
theory-driven
constructed
political
axis
is
supported
by
the
data
and
investigate
the
possibility
of
other
groupings
of
respondents
or
beliefs arising from the data.
|
2301.02734#3
|
2301.02734#5
|
2301.02734
|
2301.02734#5
|
Political, economic, and governance attitudes of blockchain users
|
1
Introduction
As blockchain technology has evolved over more than a decade, cryptocurrencies and
crypto-economic systems have had a growing impact on the world.
|
2301.02734#4
|
2301.02734#6
|
2301.02734
|
2301.02734#6
|
Political, economic, and governance attitudes of blockchain users
|
Millions of people have involved
themselves in crypto
1
: as of 2021, around 15 percent
of American adults have reported owning
cryptocurrency (Perrin 2021), and many other countries have even higher adoption rates (Buchholz
2021).
|
2301.02734#5
|
2301.02734#7
|
2301.02734
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2301.02734#7
|
Political, economic, and governance attitudes of blockchain users
|
The past few years have seen the growth of decentralized apps and the crypto startup industry .
|
2301.02734#6
|
2301.02734#8
|
2301.02734
|
2301.02734#8
|
Political, economic, and governance attitudes of blockchain users
|
Correspondingly , governments are beginning to take regulatory actions.
|
2301.02734#7
|
2301.02734#9
|
2301.02734
|
2301.02734#9
|
Political, economic, and governance attitudes of blockchain users
|
Also, even as blockchain
ecosystems move towards less computationally-intensive consensus mechanisms, the ongoing
environmental impact of blockchain use is huge.
|
2301.02734#8
|
2301.02734#10
|
2301.02734
|
2301.02734#10
|
Political, economic, and governance attitudes of blockchain users
|
Given the impact of crypto-economic activity on individuals and on shared resources, it is
increasingly important to understand how its users are relating to the technology .
|
2301.02734#9
|
2301.02734#11
|
2301.02734
|
2301.02734#11
|
Political, economic, and governance attitudes of blockchain users
|
While the hard data
of cryptocurrency transactions and account balances is often publicly available by design, users’
1
Throughout the text, we use the term “crypto” to
encompass blockchain technologies such as
cryptocurrencies and the communities and ideologies which drive their development and use.
|
2301.02734#10
|
2301.02734#12
|
2301.02734
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2301.02734#12
|
Political, economic, and governance attitudes of blockchain users
|
1
motivations for engaging with crypto are more opaque.
|
2301.02734#11
|
2301.02734#13
|
2301.02734
|
2301.02734#13
|
Political, economic, and governance attitudes of blockchain users
|
There is little existing data on the stated
beliefs or attitudes of the variety of people using blockchain technologies.
|
2301.02734#12
|
2301.02734#14
|
2301.02734
|
2301.02734#14
|
Political, economic, and governance attitudes of blockchain users
|
What do blockchain users
believe about the economic, political, and social relevance of crypto?
|
2301.02734#13
|
2301.02734#15
|
2301.02734
|
2301.02734#15
|
Political, economic, and governance attitudes of blockchain users
|
While there has been attention
to the attitudes of the general population towards cryptocurrencies and blockchain technology (Perrin
2021; “Global State of Crypto, 2022” 2022), there is also a need to understand the beliefs of active
participants of blockchain ecosystems.
|
2301.02734#14
|
2301.02734#16
|
2301.02734
|
2301.02734#16
|
Political, economic, and governance attitudes of blockchain users
|
What do blockchain ecosystem participants believe about how the technology is being – or should be
– developed, used, and regulated?
|
2301.02734#15
|
2301.02734#17
|
2301.02734
|
2301.02734#17
|
Political, economic, and governance attitudes of blockchain users
|
Are there discrete types of crypto contributors, or is there a
spectrum of beliefs?
|
2301.02734#16
|
2301.02734#18
|
2301.02734
|
2301.02734#18
|
Political, economic, and governance attitudes of blockchain users
|
What specific beliefs are most relevant in distinguishing respondents between
types or along axes?
|
2301.02734#17
|
2301.02734#19
|
2301.02734
|
2301.02734#19
|
Political, economic, and governance attitudes of blockchain users
|
This work is a first step in the development of a framework for thinking about
this spectrum or grouping of beliefs in crypto.
|
2301.02734#18
|
2301.02734#20
|
2301.02734
|
2301.02734#20
|
Political, economic, and governance attitudes of blockchain users
|
We report the results of a lar ge-scale survey of participants in the blockchain economy .
|
2301.02734#19
|
2301.02734#21
|
2301.02734
|
2301.02734#21
|
Political, economic, and governance attitudes of blockchain users
|
The survey
was designed to shed light on respondents’ socioeconomic and sociopolitical beliefs relating to
crypto, economic modes of engagement with crypto, and attitudes towards governance of blockchain
technology .
|
2301.02734#20
|
2301.02734#22
|
2301.02734
|
2301.02734#22
|
Political, economic, and governance attitudes of blockchain users
|
We describe the distributions of these responses and their relationships to self-reported
political ideology and specific crypto ecosystems such as Bitcoin and Ethereum.
|
2301.02734#21
|
2301.02734#23
|
2301.02734
|
2301.02734#23
|
Political, economic, and governance attitudes of blockchain users
|
We also evaluate the survey instrument itself: are the questions able to assess distinct and relevant
facets of beliefs?
|
2301.02734#22
|
2301.02734#24
|
2301.02734
|
2301.02734#24
|
Political, economic, and governance attitudes of blockchain users
|
Can we identify underlying factors which describe broader groupings of beliefs?
|
2301.02734#23
|
2301.02734#25
|
2301.02734
|
2301.02734#25
|
Political, economic, and governance attitudes of blockchain users
|
Using factor analysis methods, we find that a political axis and corresponding typology , informed by
the Pew Research Center ’s Political Typology Quiz, meaningfully describes variation between
respondents.
|
2301.02734#24
|
2301.02734#26
|
2301.02734
|
2301.02734#26
|
Political, economic, and governance attitudes of blockchain users
|
2
Backgr ound
While there is no existing political theory of crypto per se, there are substantial ethnographic studies
of crypto communities (and related digital communities) that address the political dimensions of
crypto.
|
2301.02734#25
|
2301.02734#27
|
2301.02734
|
2301.02734#27
|
Political, economic, and governance attitudes of blockchain users
|
For example, ethnographic studies have informed the creation of a proposed political
typology of blockchain projects (Husain, Franklin, and Roep 2020), reflecting earlier ideas on the
“intrinsic” political values of technical artifacts (W inner 1980).
|
2301.02734#26
|
2301.02734#28
|
2301.02734
|
2301.02734#28
|
Political, economic, and governance attitudes of blockchain users
|
In this vein, cryptocurrencies have
been characterized as realizations of crypto-anarchist values such as privacy and autonomy (Chohan
2017; Beltramini 2021), following in the footsteps of earlier cypherpunk writings (Hughes 1993;
May 1994) as well as the original Bitcoin whitepaper (Nakamoto 2008).
|
2301.02734#27
|
2301.02734#29
|
2301.02734
|
2301.02734#29
|
Political, economic, and governance attitudes of blockchain users
|
Other ethnographies have
described issues of on- and of f-chain governance (De Filippi and Loveluck 2016) and the political
motivations and cultural context of projects such as Bitcoin (Golumbia 2016) and Ethereum (Brody
and Couture 2021).
|
2301.02734#28
|
2301.02734#30
|
2301.02734
|
2301.02734#30
|
Political, economic, and governance attitudes of blockchain users
|
A previous industry survey , conducted by CoinDesk in 2018, contained several questions related to
politics and governance (R yan 2018; Bauerle and R yan 2018), though the questions focused more
specifically on individual projects and topical questions such as reactions to SEC rulings on the
securitization status of Ethereum.
|
2301.02734#29
|
2301.02734#31
|
2301.02734
|
2301.02734#31
|
Political, economic, and governance attitudes of blockchain users
|
Distinct from questions about political values, the topic of blockchain governance—including the
relationship between blockchains and traditional governments—is one of the most salient and
polarizing questions in crypto, one that has led to the creation, forking, and dissolution of many
projects.
|
2301.02734#30
|
2301.02734#32
|
2301.02734
|
2301.02734#32
|
Political, economic, and governance attitudes of blockchain users
|
While we cannot recount all the major positions here (some of which are reflected in the
survey itself; see “Methodology”), there is a broad distinction between approaches that emphasize
on-chain governance and those that emphasize of f-chain governance.
|
2301.02734#31
|
2301.02734#33
|
2301.02734
|
2301.02734#33
|
Political, economic, and governance attitudes of blockchain users
|
A number of academic analyses
2
have studied these dif ferent approaches to blockchain governance (Reijers, O’Brolcháin, and Haynes
2016; Liu et al.
|
2301.02734#32
|
2301.02734#34
|
2301.02734
|
2301.02734#34
|
Political, economic, and governance attitudes of blockchain users
|
2021; van Pelt et al.
|
2301.02734#33
|
2301.02734#35
|
2301.02734
|
2301.02734#35
|
Political, economic, and governance attitudes of blockchain users
|
2021), along with a vastly greater number of industry manifestos
and opinion pieces (Zamfir 2019; Szabo 1996).
|
2301.02734#34
|
2301.02734#36
|
2301.02734
|
2301.02734#36
|
Political, economic, and governance attitudes of blockchain users
|
3
Methodology
3.1
Survey questions
The survey consists of 19 questions related to respondents’ crypto-related beliefs and activities, with
three types of questions interspersed: those eliciting opinions about the political dimensions of crypto
activity (“crypto-political”), those eliciting economics opinions (“crypto-economic”), and those
eliciting attitudes about the governance of crypto projects (“crypto-governance”).
|
2301.02734#35
|
2301.02734#37
|
2301.02734
|
2301.02734#37
|
Political, economic, and governance attitudes of blockchain users
|
All questions were
multiple choice, with 2-4 possible selections, and the respondent could opt not to answer .
|
2301.02734#36
|
2301.02734#38
|
2301.02734
|
2301.02734#38
|
Political, economic, and governance attitudes of blockchain users
|
See Table 1
for the full list of questions.
|
2301.02734#37
|
2301.02734#39
|
2301.02734
|
2301.02734#39
|
Political, economic, and governance attitudes of blockchain users
|
The survey questions and provided choices included both a formal portion drawing from existing
political survey instruments and a more exploratory portion intended to elicit beliefs relevant to a
general crypto-political typology .
|
2301.02734#38
|
2301.02734#40
|
2301.02734
|
2301.02734#40
|
Political, economic, and governance attitudes of blockchain users
|
In particular , a few of the questions selected (Q1 1-13, Q15, Q19),
were based on questions from Pew’ s Political Typology Quiz (Nadeem 2021) and intended to relate
to political sentiment.
|
2301.02734#39
|
2301.02734#41
|
2301.02734
|
2301.02734#41
|
Political, economic, and governance attitudes of blockchain users
|
Other questions (e.g., Q1, Q17) were developed in collaboration with a number
of community members in crypto, drawing on the culture, memes, and references common in crypto.
|
2301.02734#40
|
2301.02734#42
|
2301.02734
|
2301.02734#42
|
Political, economic, and governance attitudes of blockchain users
|
Altogether , the content was designed to elicit respondents' primary modes of economic engagement
with crypto, their political sentiment, and opinions as to how crypto communities themselves should
be governed.
|
2301.02734#41
|
2301.02734#43
|
2301.02734
|
2301.02734#43
|
Political, economic, and governance attitudes of blockchain users
|
3.2
Construction of political “types” and identification of “axes” of belief
Our choice to identify separate “axes” of economic, political, and governance beliefs were based on
discussion with community members and in analogy to existing classifications such as the traditional
“left-right” political axis.
|
2301.02734#42
|
2301.02734#44
|
2301.02734
|
2301.02734#44
|
Political, economic, and governance attitudes of blockchain users
|
For one of these, the political axis, we also leveraged our study design to
group and relate questions more directly by defining a continuous construct intended to assess
respondents' crypto-political leanings.
|
2301.02734#43
|
2301.02734#45
|
2301.02734
|
2301.02734#45
|
Political, economic, and governance attitudes of blockchain users
|
We identified a subset of questions as most relevant to political
orientation, and computed a score for each participant by summing the responses to these questions
(coded with values in the range [-1, 2] as described in Table 1) in analogy to the Pew methodology
(Nadeem 2021).
|
2301.02734#44
|
2301.02734#46
|
2301.02734
|
2301.02734#46
|
Political, economic, and governance attitudes of blockchain users
|
The lowest and highest scores on this political “axis” were designed to highlight
extreme positions of collectivist and anarcho-capitalist approaches to using blockchain technology .
|
2301.02734#45
|
2301.02734#47
|
2301.02734
|
2301.02734#47
|
Political, economic, and governance attitudes of blockchain users
|
Five discrete types were defined by thresholds in the score according to Table 2:
crypto-anarcho-capitalist, crypto-libertarian, centrist, crypto-communitarian, and crypto-leftist; these
types were developed both with definitions from the Pew typologies and with input from the
community .
|
2301.02734#46
|
2301.02734#48
|
2301.02734
|
2301.02734#48
|
Political, economic, and governance attitudes of blockchain users
|
3.3
Recruitment
We relied on a convenience (self-selected) sample of participants in the crypto community .
|
2301.02734#47
|
2301.02734#49
|
2301.02734
|
2301.02734#49
|
Political, economic, and governance attitudes of blockchain users
|
Participants were recruited by distributing the survey through blockchain-focused forums and
listservs, conferences (LisCon and ETHDenver), social media posts, and articles published on
blockchain-focused news sites.
|
2301.02734#48
|
2301.02734#50
|
2301.02734
|
2301.02734#50
|
Political, economic, and governance attitudes of blockchain users
|
We motivated voluntary participant engagement with two strategies.
|
2301.02734#49
|
2301.02734#51
|
2301.02734
|
2301.02734#51
|
Political, economic, and governance attitudes of blockchain users
|
We presented the survey as a
quiz that assigned respondents one out of an entertaining typology of “types” on the basis of their
3
responses (“crypto-leftist,” “cryptopunk,” etc.) immediately upon completion of the survey .
|
2301.02734#50
|
2301.02734#52
|
2301.02734
|
2301.02734#52
|
Political, economic, and governance attitudes of blockchain users
|
Stylized
as “factions”, the crypto-political types corresponded to the political types we defined based on the
Pew typology , while the crypto-economic and crypto-governance types were constructed by using
thresholds to partition respondents into five ad hoc types (for more detail, see Section 1.1 of the
Supplementary Material).
|
2301.02734#51
|
2301.02734#53
|
2301.02734
|
2301.02734#53
|
Political, economic, and governance attitudes of blockchain users
|
We also incentivized survey completion with the opportunity to receive a
non-fungible token (NFT) corresponding to their assigned “type”, contingent upon their provision of
a valid Ethereum wallet address or ENS name.
|
2301.02734#52
|
2301.02734#54
|
2301.02734
|
2301.02734#54
|
Political, economic, and governance attitudes of blockchain users
|
3.4
Analysis
To survey the overall landscape of crypto-political beliefs, we observed the distribution of choices
selected by respondents.
|
2301.02734#53
|
2301.02734#55
|
2301.02734
|
2301.02734#55
|
Political, economic, and governance attitudes of blockchain users
|
We aggregated these responses for each question, including the null
response of no choice selected, and computed the mar gins of error for a 95% confidence interval,
assuming a random sample of the population.
|
2301.02734#54
|
2301.02734#56
|
2301.02734
|
2301.02734#56
|
Political, economic, and governance attitudes of blockchain users
|
To investigate how political self-identification and participation in specific blockchain ecosystems
related to beliefs, we grouped participants by their responses to the corresponding questions.
|
2301.02734#55
|
2301.02734#57
|
2301.02734
|
2301.02734#57
|
Political, economic, and governance attitudes of blockchain users
|
We then
determined which questions displayed a statistically significant dif ference in the distribution of
responses between these groups.
|
2301.02734#56
|
2301.02734#58
|
2301.02734
|
2301.02734#58
|
Political, economic, and governance attitudes of blockchain users
|
We also wanted to understand which questions were most meaningful in dif ferentiating respondents.
|
2301.02734#57
|
2301.02734#59
|
2301.02734
|
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