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id int64 1 200 | period int64 1 52 | equilibrium_gap float64 0.07 1 | adjustment_lag float64 0.13 0.92 | capacity_constraint float64 0.12 0.97 | coordination_failure float64 0.1 0.74 | expectation_dispersion float64 0.1 0.73 | policy_response_delay float64 0.1 1 | adaptive_capacity float64 0.04 0.88 | equilibrift_index float64 0.29 0.7 |
|---|---|---|---|---|---|---|---|---|---|
1 | 21 | 0.490917 | 0.443558 | 0.500596 | 0.295814 | 0.277664 | 0.589255 | 0.575334 | 0.437159 |
2 | 25 | 0.196986 | 0.424057 | 0.810188 | 0.532093 | 0.178264 | 0.098695 | 0.299678 | 0.414637 |
3 | 4 | 0.614729 | 0.473727 | 0.395204 | 0.384573 | 0.342013 | 0.340162 | 0.619524 | 0.435724 |
4 | 48 | 0.792377 | 0.476991 | 0.436184 | 0.436173 | 0.384226 | 0.467441 | 0.339566 | 0.533891 |
5 | 22 | 0.573692 | 0.600484 | 0.631034 | 0.553417 | 0.485514 | 0.490181 | 0.356175 | 0.570725 |
6 | 30 | 0.447372 | 0.329499 | 0.589502 | 0.35485 | 0.272089 | 0.859788 | 0.284135 | 0.493605 |
7 | 37 | 0.494721 | 0.359696 | 0.824096 | 0.316616 | 0.260121 | 0.564922 | 0.778154 | 0.453867 |
8 | 41 | 0.252555 | 0.421517 | 0.701658 | 0.456444 | 0.34775 | 0.705538 | 0.219838 | 0.498532 |
9 | 41 | 0.459808 | 0.483336 | 0.315325 | 0.466803 | 0.448767 | 0.84464 | 0.324192 | 0.50789 |
10 | 38 | 0.538878 | 0.418262 | 0.816848 | 0.599632 | 0.297462 | 0.65553 | 0.455292 | 0.558172 |
11 | 8 | 0.686398 | 0.635993 | 0.749209 | 0.524599 | 0.244932 | 0.801615 | 0.792655 | 0.578676 |
12 | 26 | 0.523241 | 0.411764 | 0.695399 | 0.427643 | 0.483774 | 0.511867 | 0.38464 | 0.522677 |
13 | 30 | 0.698939 | 0.294212 | 0.6216 | 0.458092 | 0.460023 | 0.702912 | 0.697517 | 0.520251 |
14 | 22 | 0.692609 | 0.371247 | 0.651625 | 0.406538 | 0.29728 | 0.60232 | 0.702516 | 0.496797 |
15 | 40 | 0.371294 | 0.32355 | 0.262453 | 0.221212 | 0.312689 | 0.144139 | 0.139895 | 0.339819 |
16 | 28 | 0.664108 | 0.499008 | 0.82242 | 0.574812 | 0.309645 | 0.895501 | 0.348487 | 0.634493 |
17 | 30 | 0.604427 | 0.393258 | 0.566929 | 0.379535 | 0.179121 | 0.712939 | 0.265658 | 0.508132 |
18 | 18 | 0.484378 | 0.238248 | 0.874286 | 0.454458 | 0.413651 | 0.612976 | 0.85652 | 0.476049 |
19 | 11 | 0.369236 | 0.713972 | 0.361056 | 0.481536 | 0.357446 | 0.465457 | 0.53266 | 0.458749 |
20 | 52 | 0.845859 | 0.549133 | 0.763063 | 0.43336 | 0.496237 | 0.686772 | 0.46611 | 0.635143 |
21 | 15 | 0.723092 | 0.745302 | 0.738445 | 0.712234 | 0.382103 | 0.450157 | 0.101288 | 0.671473 |
22 | 25 | 0.50889 | 0.769586 | 0.56302 | 0.492408 | 0.48062 | 0.350689 | 0.352445 | 0.548445 |
23 | 27 | 0.300983 | 0.582285 | 0.344383 | 0.40376 | 0.378378 | 0.292354 | 0.371292 | 0.408349 |
24 | 5 | 0.288137 | 0.403108 | 0.660169 | 0.36255 | 0.281981 | 0.335491 | 0.828964 | 0.369709 |
25 | 5 | 0.661798 | 0.584085 | 0.826026 | 0.610527 | 0.447773 | 0.850928 | 0.875699 | 0.611725 |
26 | 29 | 0.471401 | 0.558214 | 0.611378 | 0.414782 | 0.4244 | 0.633921 | 0.476154 | 0.518867 |
27 | 8 | 0.636347 | 0.582831 | 0.87672 | 0.623262 | 0.228661 | 0.749317 | 0.426352 | 0.622776 |
28 | 44 | 0.943982 | 0.263949 | 0.267089 | 0.297931 | 0.360021 | 0.756047 | 0.38996 | 0.510405 |
29 | 7 | 0.310369 | 0.401317 | 0.607063 | 0.518335 | 0.435617 | 0.295865 | 0.708997 | 0.41286 |
30 | 28 | 0.68485 | 0.585928 | 0.620323 | 0.354109 | 0.335424 | 0.793233 | 0.600285 | 0.554956 |
31 | 36 | 0.575727 | 0.348965 | 0.42926 | 0.211428 | 0.236666 | 0.665971 | 0.457182 | 0.43186 |
32 | 44 | 0.305538 | 0.380728 | 0.559085 | 0.200305 | 0.196936 | 0.613928 | 0.443676 | 0.392456 |
33 | 19 | 0.571518 | 0.400082 | 0.662237 | 0.46472 | 0.233914 | 1 | 0.417994 | 0.555606 |
34 | 27 | 0.649678 | 0.309455 | 0.319875 | 0.321215 | 0.2475 | 0.692381 | 0.239526 | 0.464432 |
35 | 45 | 0.636954 | 0.593223 | 0.971326 | 0.547757 | 0.290309 | 0.391142 | 0.420507 | 0.594128 |
36 | 7 | 0.78358 | 0.550928 | 0.797258 | 0.3926 | 0.280153 | 0.853351 | 0.216638 | 0.641746 |
37 | 36 | 0.498507 | 0.379209 | 0.667513 | 0.411104 | 0.41418 | 0.363042 | 0.758229 | 0.442175 |
38 | 36 | 0.484264 | 0.695453 | 0.613679 | 0.343174 | 0.413614 | 0.821899 | 0.058007 | 0.596819 |
39 | 17 | 0.622611 | 0.470316 | 0.641959 | 0.336032 | 0.141053 | 0.506454 | 0.206738 | 0.506558 |
40 | 23 | 0.51209 | 0.370276 | 0.409612 | 0.182453 | 0.266067 | 1 | 0.293866 | 0.475285 |
41 | 25 | 0.780835 | 0.445299 | 0.763767 | 0.412892 | 0.540823 | 0.698782 | 0.318431 | 0.624332 |
42 | 32 | 0.511859 | 0.192424 | 0.857869 | 0.382054 | 0.242881 | 0.279942 | 0.310438 | 0.455601 |
43 | 38 | 0.62577 | 0.704443 | 0.803996 | 0.506136 | 0.42513 | 0.659726 | 0.734487 | 0.594097 |
44 | 10 | 0.716755 | 0.668829 | 0.763086 | 0.509141 | 0.291437 | 0.821687 | 0.521425 | 0.625169 |
45 | 22 | 0.79707 | 0.408132 | 0.66755 | 0.520677 | 0.355007 | 0.546842 | 0.247088 | 0.587931 |
46 | 5 | 0.814875 | 0.673401 | 0.196532 | 0.369746 | 0.702405 | 0.754053 | 0.601006 | 0.568603 |
47 | 23 | 0.508527 | 0.417458 | 0.372206 | 0.538797 | 0.240634 | 0.732479 | 0.407597 | 0.479497 |
48 | 8 | 0.336553 | 0.439586 | 0.327727 | 0.193632 | 0.335844 | 0.645629 | 0.482813 | 0.386685 |
49 | 25 | 0.529825 | 0.62248 | 0.916602 | 0.573714 | 0.316697 | 0.727661 | 0.435231 | 0.614338 |
50 | 34 | 0.807361 | 0.592775 | 0.81547 | 0.407572 | 0.433464 | 0.906212 | 0.474784 | 0.657134 |
51 | 23 | 0.368185 | 0.38644 | 0.670201 | 0.369373 | 0.36781 | 0.531265 | 0.742937 | 0.428007 |
52 | 47 | 0.665069 | 0.56774 | 0.695121 | 0.453255 | 0.381188 | 0.918739 | 0.474204 | 0.607098 |
53 | 40 | 0.967584 | 0.494645 | 0.697906 | 0.412239 | 0.50943 | 0.711428 | 0.252882 | 0.663253 |
54 | 30 | 0.67602 | 0.484379 | 0.573893 | 0.483197 | 0.504876 | 0.497765 | 0.832828 | 0.509209 |
55 | 38 | 0.562147 | 0.668776 | 0.547871 | 0.576829 | 0.401953 | 0.505888 | 0.260831 | 0.570707 |
56 | 11 | 0.266934 | 0.408437 | 0.553526 | 0.308761 | 0.36799 | 0.334683 | 0.627547 | 0.372093 |
57 | 17 | 0.558212 | 0.477621 | 0.431607 | 0.197335 | 0.294373 | 0.788711 | 0.523982 | 0.462318 |
58 | 38 | 0.504584 | 0.426656 | 0.349436 | 0.510154 | 0.514518 | 0.488657 | 0.298008 | 0.487093 |
59 | 16 | 0.698915 | 0.507499 | 0.609594 | 0.494669 | 0.728763 | 0.748375 | 0.363856 | 0.628642 |
60 | 10 | 0.768817 | 0.327115 | 0.676204 | 0.466226 | 0.415235 | 0.508581 | 0.234283 | 0.566996 |
61 | 32 | 0.476419 | 0.359111 | 0.696475 | 0.544672 | 0.481233 | 0.550915 | 0.268106 | 0.537479 |
62 | 11 | 0.572204 | 0.521309 | 0.692791 | 0.383644 | 0.242914 | 0.331395 | 0.832561 | 0.448068 |
63 | 45 | 0.626896 | 0.604456 | 0.447268 | 0.442074 | 0.318331 | 0.44785 | 0.286557 | 0.518832 |
64 | 6 | 0.583938 | 0.615753 | 0.910319 | 0.392235 | 0.357197 | 0.604515 | 0.49511 | 0.581766 |
65 | 4 | 0.451496 | 0.480475 | 0.86213 | 0.691718 | 0.358033 | 0.706882 | 0.677758 | 0.561971 |
66 | 12 | 0.730234 | 0.471695 | 0.528106 | 0.472447 | 0.240507 | 0.536617 | 0.271135 | 0.538299 |
67 | 44 | 0.658996 | 0.453831 | 0.743919 | 0.601197 | 0.47748 | 0.516551 | 0.171994 | 0.609691 |
68 | 27 | 0.266948 | 0.582923 | 0.214907 | 0.285612 | 0.184735 | 0.432007 | 0.435601 | 0.351477 |
69 | 20 | 0.507395 | 0.683577 | 0.599786 | 0.460112 | 0.417044 | 0.549291 | 0.514608 | 0.535732 |
70 | 38 | 0.622012 | 0.504037 | 0.402001 | 0.323471 | 0.281611 | 0.446252 | 0.63109 | 0.438889 |
71 | 39 | 0.471091 | 0.364472 | 0.299578 | 0.275873 | 0.19554 | 0.270246 | 0.179552 | 0.377028 |
72 | 16 | 0.209826 | 0.413201 | 0.790353 | 0.386203 | 0.381405 | 0.368026 | 0.597446 | 0.41879 |
73 | 4 | 0.649762 | 0.411836 | 0.597395 | 0.591176 | 0.333363 | 0.798427 | 0.310104 | 0.578998 |
74 | 42 | 0.408139 | 0.389604 | 0.265308 | 0.286755 | 0.322156 | 0.90179 | 0.520662 | 0.421367 |
75 | 18 | 0.612386 | 0.381358 | 0.503782 | 0.264896 | 0.095479 | 0.315943 | 0.410637 | 0.409492 |
76 | 4 | 0.578579 | 0.479856 | 0.35511 | 0.415101 | 0.221714 | 0.516077 | 0.591301 | 0.436829 |
77 | 26 | 0.264424 | 0.1619 | 0.348211 | 0.150731 | 0.449076 | 0.525332 | 0.835191 | 0.289015 |
78 | 20 | 0.822345 | 0.615475 | 0.695799 | 0.649206 | 0.4479 | 0.550123 | 0.657514 | 0.619173 |
79 | 29 | 0.565435 | 0.341566 | 0.492269 | 0.600145 | 0.443436 | 0.796204 | 0.781696 | 0.501108 |
80 | 32 | 0.342554 | 0.410342 | 0.512296 | 0.386059 | 0.181879 | 0.79182 | 0.350652 | 0.45196 |
81 | 7 | 0.527824 | 0.407798 | 0.592027 | 0.557459 | 0.304477 | 0.925876 | 0.105061 | 0.580717 |
82 | 5 | 0.64144 | 0.67162 | 0.742269 | 0.503905 | 0.255587 | 0.59825 | 0.832079 | 0.54431 |
83 | 30 | 0.848113 | 0.467413 | 0.369037 | 0.370607 | 0.393325 | 0.292161 | 0.360318 | 0.501566 |
84 | 50 | 0.530524 | 0.701676 | 0.490983 | 0.521724 | 0.09681 | 0.732026 | 0.56575 | 0.512857 |
85 | 13 | 0.894246 | 0.681456 | 0.732084 | 0.571136 | 0.38994 | 0.685774 | 0.141602 | 0.6999 |
86 | 19 | 0.489856 | 0.282806 | 0.840985 | 0.286558 | 0.251864 | 0.713376 | 0.25428 | 0.508297 |
87 | 15 | 0.52303 | 0.40264 | 0.603111 | 0.311814 | 0.365039 | 0.614525 | 0.470891 | 0.479638 |
88 | 12 | 0.626461 | 0.626616 | 0.469077 | 0.296549 | 0.231225 | 0.693686 | 0.680936 | 0.485015 |
89 | 8 | 0.541583 | 0.514837 | 0.348149 | 0.360899 | 0.379334 | 0.194386 | 0.691991 | 0.396568 |
90 | 13 | 0.972295 | 0.562362 | 0.329423 | 0.383875 | 0.481618 | 0.688636 | 0.647631 | 0.566555 |
91 | 48 | 0.672586 | 0.602223 | 0.651006 | 0.447077 | 0.426237 | 0.439764 | 0.616716 | 0.539873 |
92 | 29 | 0.700275 | 0.520367 | 0.441895 | 0.540185 | 0.257266 | 0.521027 | 0.439205 | 0.519118 |
93 | 42 | 0.623559 | 0.743613 | 0.687152 | 0.430978 | 0.459771 | 0.599275 | 0.512053 | 0.589851 |
94 | 31 | 0.606021 | 0.575653 | 0.602448 | 0.530465 | 0.394418 | 0.724493 | 0.50128 | 0.568107 |
95 | 33 | 0.445229 | 0.430939 | 0.34636 | 0.376603 | 0.32517 | 0.57774 | 0.452027 | 0.429285 |
96 | 4 | 0.912693 | 0.562752 | 0.729175 | 0.685312 | 0.310002 | 0.656412 | 0.417903 | 0.65937 |
97 | 43 | 0.658527 | 0.552291 | 0.377971 | 0.447445 | 0.257941 | 0.717081 | 0.175086 | 0.542684 |
98 | 25 | 0.538937 | 0.532728 | 0.716946 | 0.536659 | 0.388254 | 0.384115 | 0.413654 | 0.534186 |
99 | 5 | 0.586709 | 0.818056 | 0.780987 | 0.463063 | 0.345492 | 0.655903 | 0.536651 | 0.60452 |
100 | 22 | 0.733294 | 0.256881 | 0.654888 | 0.423066 | 0.18991 | 0.70364 | 0.584305 | 0.500567 |
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Equilibrift Economics Dataset
Dataset Description
Summary
Synthetic 200-row dataset for Equilibrift measurement and computational experiments.
Supported Tasks
- Economic analysis
- Computational Economics research
- Computational economics
Languages
- English (metadata and documentation)
- Python (code examples)
Dataset Structure
Data Fields
id: Unique observation idperiod: Synthetic adjustment periodequilibrium_gap: Distance between observed state and model-implied equilibriumadjustment_lag: Lag in quantity and price adjustmentcapacity_constraint: Binding production or logistics capacity constraintscoordination_failure: Coordination breakdown intensity among agentsexpectation_dispersion: Cross-agent dispersion in expectationspolicy_response_delay: Delay in stabilizing policy responseadaptive_capacity: System ability to adapt toward equilibriumequilibrift_index: Composite term index
Data Splits
- Full dataset: 200 examples
Dataset Creation
Source Data
Synthetic data generated for demonstrating Equilibrift applications.
Data Generation
Channels are sampled from controlled distributions with correlated structure. The term index is computed from normalized channels and directional weights.
Considerations
Social Impact
Research-only synthetic data for method development and reproducibility testing.
Additional Information
Licensing
MIT License - free for academic and commercial use.
Citation
@dataset{equilibrift2026, title={{Equilibrift Economics Dataset}}, author={{Economic Research Collective}}, year={{2026}} }
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