0.14.1

Major Changes

none

Minor Changes

• Fixes a bug in make_figs arising from the metadata argument being incompatible with jpg. #1386
• Reverts behavior of the repr method of the Model class, so that long strings aren't generated. Full description is available with describe(). #1390

0.14.0

Major Changes

• Adds HARK.core.AgentPopulation class to represent a population of agents with ex-ante heterogeneous parametrizations as distributions. #1237
• Adds HARK.core.Parameters class to represent a collection of time varying and time invariant parameters in a model. #1240
• Adds HARK.simulation.monte_carlo module for generic Monte Carlo simulation functions using Python model configurations. 1296

Minor Changes

• Adds option sim_common_Rrisky to control whether risky-asset models draw common or idiosyncratic returns in simulation. #1250,#1253
• Addresses #1255. Makes age-varying stochastic returns possible and draws from their discretized version. #1262
• Fixes bug in the metric that compares dictionaries with the same keys. #1260
• Fixes bug in the calc_jacobian method. #1342
• Fixes bug that prevented risky-asset consumer types from working with time-varying interest rates Rfree. 1343
• Overhauls and expands condition checking for the ConsIndShock model #1294. Condition values and a description of their interpretation is stored in the bilt dictionary of IndShockConsumerType.
• Creates a models/ directory with Python model configurations for perfect foresight and Fisher 2-period models. 1347
• Fixes bug in AgentType simulations where 'who_dies' for period t was being recorded in period t-1 in the history Carlo simulation functions using Python model configurations.1296
• Removes unused simulation.py .1296
• Fixes bug that default seed was being used in the initializing of income shock distributions. 1380

0.13.0

Major Changes

• Updates the DCEGM tools to address the flaws identified in issue #1062. PR: 1100.
• Updates IndexDstn, introducing the option to use an existing RNG instead of creating a new one, and creating and storing all the conditional distributions at initialization. 1104
• make_shock_history and read_shocks == True now store and use the random draws that determine newborn's initial states #1101.
• FrameModel and FrameSet classes introduced for more modular construction of framed models. FrameAgentType dedicated to simulation. #1117
• General control transitions based on decision rules in FrameAgentType. #1117
• Adds distr_of_function tool to calculate the distribution of a function of a discrete random variable. #1144
• Changes the DiscreteDistribution class to allow for arbitrary array-valued random variables. #1146
• Adds IndShockRiskyAssetConsumerType as agent which can invest savings all in safe asset, all in risky asset, a fixed share in risky asset, or optimize its portfolio. #1107
• Updates all HARK models to allow for age-varying interest rates. #1150
• Adds DiscreteDistribution.expected method which expects vectorized functions and is faster than HARK.distribution.calc_expectation. #1156
• Adds DiscreteDistributionXRA class which extends DiscreteDistribution to allow for underlying data to be stored in a xarray.DataArray object. #1156
• Adds keyword argument labels to expected() when using DiscreteDistributionXRA to allow for expressive functions that use labeled xarrays. #1156
• Adds a wrapper for interpolation.py for fast multilinear interpolation. #1151
• Adds support for the calculation of dreivatives in the interpolation.py wrappers. #1157
• Adds class DecayInterp to econforgeinterp.py. It implements interpolators that "decay" to some limiting function when extrapolating. #1165
• Add methods to non stochastically simulate an economy by computing transition matrices. Functions to compute transition matrices and ergodic distribution have been added #1155.
• Fixes a bug that causes t_age and t_cycle to get out of sync when reading pre-computed mortality. #1181
• Adds Methods to calculate Heterogenous Agent Jacobian matrices. #1185
• Enhances combine_indep_dstns to work with labeled distributions (DiscreteDistributionLabeled). #1191
• Updates the numpy random generator from RandomState to Generator. #1193
• Turns the income and income+return distributions into DiscreteDistributionLabeled objects. #1189
• Creates UtilityFuncCRRA which is an object oriented utility function with a coefficient of constant relative risk aversion and includes derivatives and inverses. Also creates UtilityFuncCobbDouglas, UtilityFuncCobbDouglasCRRA, and UtilityFuncConstElastSubs. #1168
• Reorganizes HARK.distribution. All distributions now inherit all features from scipy.stats. New ContinuousFrozenDistribution and DiscreteFrozenDistribution to use scipy.stats distributions not yet implemented in HARK. New Distribution.discretize(N, method = "***") replaces Distribution.approx(N). New DiscreteDistribution.limit attribute describes continuous origin and discretization method. #1197.
• Creates new class of labeled models under ConsLabeledModel that use xarray for more expressive modeling of underlying mathematical and economics variables. #1177

Minor Changes

• Updates the lognormal-income-process constructor from ConsIndShockModel.py to use IndexDistribution. #1024, #1115
• Allows for age-varying unemployment probabilities and replacement incomes with the lognormal income process constructor. #1112
• Option to have newborn IndShockConsumerType agents with a transitory income shock in the first period. Default is false, meaning they only have a permanent income shock in period 1 and permanent AND transitory in the following ones. #1126
• Adds benchmark utility to profile the performance of HARK solvers. #1131
• Fixes scaling bug in Normal equiprobable approximation method. 1139
• Removes the extra-dimension that was returned by calc_expectations in some instances. #1149
• Adds HARK.distribution.expected alias for DiscreteDistribution.expected. #1156
• Renames attributes in DiscreteDistribution: X to atoms and pmf to pmv. #1164, #1051, #1159.
• Remove or replace automated tests that depend on brittle simulation results. #1148
• Updates asset grid constructor from ConsIndShockModel.py to allow for linearly-spaced grids when aXtraNestFac == -1. #1172
• Renames DiscreteDistributionXRA to DiscreteDistributionLabeled and updates methods #1170
• Renames HARK.numba to HARK.numba_tools #1183
• Adds the RNG seed as a property of DiscreteDistributionLabeled #1184
• Updates the approx method of HARK.distributions.Uniform to include the endpoints of the distribution with infinitesimally small (zero) probability mass. #1180
• Refactors tests to incorporate custom precision HARK_PRECISION = 4. #1193
• Cast DiscreteDistribution.pmv attribute as a np.ndarray. #1199
• Update structure of dynamic interest rate. #1221

0.12.0

Major Changes

• FrameAgentType for modular definitions of agents #865 #1064
• Frame relationships with backward and forward references, with plotting example #1071
• PortfolioConsumerFrameType, a port of PortfolioConsumerType to use Frames #865
• Input parameters for cyclical models now indexed by t #1039
• A IndexDistribution class for representing time-indexed probability distributions #1018.
• Adds new consumption-savings-portfolio model RiskyContrib, which represents an agent who can save in risky and risk-free assets but faces
  frictions to moving funds between them. To circumvent these frictions, he has access to an income-deduction scheme to accumulate risky assets.
  PR: #832. See this forthcoming REMARK for the model's details.
• 'cycles' agent property moved from constructor argument to parameter #1031
• Uses iterated expectations to speed-up the solution of RiskyContrib when income and returns are independent #1058.
• ConsPortfolioSolver class for solving portfolio choice model replaces solveConsPortfolio method #1047
• ConsPortfolioDiscreteSolver class for solving portfolio choice model when allowed share is on a discrete grid #1047
• ConsPortfolioJointDistSolver class for solving portfolio chioce model when the income and risky return shocks are not independent #1047

Minor Changes

• Using Lognormal.from_mean_std in the forward simulation of the RiskyAsset model #1019
• Fix bug in DCEGM's primary kink finder due to numpy no longer accepting NaN in integer arrays #990.
• Add a general class for consumers who can save using a risky asset #1012.
• Add Boolean attribute 'PerfMITShk' to consumption models. When true, allows perfect foresight MIT shocks to be simulated. #1013.
• Track and update start-of-period (pre-income) risky and risk-free assets as states in the RiskyContrib model 1046.
• distribute_params now uses assign_params to create consistent output #1044
• The function that computes end-of-period derivatives of the value function was moved to the inside of ConsRiskyContrib's solver #1057
• Use np.fill(np.nan) to clear or initialize the arrays that store simulations. #1068
• Add Boolean attribute 'neutral_measure' to consumption models. When true, simulations are more precise by allowing permanent shocks to be drawn from a neutral measure (see Harmenberg 2021). #1069
• Fix mathematical limits of model example in example_ConsPortfolioModel.ipynb #1047
• Update ConsGenIncProcessModel.py to use calc_expectation method #1072
• Fix bug in calc_normal_style_pars_from_lognormal_pars due to math error. #1076
• Fix bug in distribute_params so that AgentCount parameter is updated. #1089

0.11.0

0.11.0

Release Data: March 4, 2021

Major Changes

• Converts non-mathematical code to PEP8 compliant form #953
• Adds a constructor for LogNormal distributions from mean and standard deviation #891
• Uses new LogNormal constructor in ConsPortfolioModel #891
• calcExpectations method for taking the expectation of a distribution over a function [#884](https://github.com/econ-ark/HARK/pull/884/] (#897)[https://github.com//pull/897/)
• Centralizes the definition of value, marginal value, and marginal marginal value functions that use inverse-space
  interpolation for problems with CRRA utility. See #888.
• MarkovProcess class used in ConsMarkovModel, ConsRepAgentModel, ConsAggShockModel #902 #929
• replace HARKobject base class with MetricObject and Model classes #903
• Add repr and eq methods to Model class #903
• Adds SSA life tables and methods to extract survival probabilities from them #986.
• Adds the U.S. CPI research series and tools to extract inflation adjustments from it #930.
• Adds a module for extracting initial distributions of permanent income (pLvl) and normalized assets (aNrm) from the SCF #932.
• Fix the return fields of dcegm/calcCrossPoints#909.
• Corrects location of constructor documentation to class string for Sphinx rendering #908
• Adds a module with tools for parsing and using various income calibrations from the literature. It includes the option of using life-cycle profiles of income shock variances from Sabelhaus and Song (2010). See #921, #941, #980.
• remove "Now" from model variable names #936
• remove Model.call; use Model init in Market and AgentType init to standardize on parameters dictionary #947
• Moves state MrkvNow to shocks['Mrkv'] in AggShockMarkov and KrusellSmith models #935
• Replaces ConsIndShock's init_lifecycle with an actual life-cycle calibration #951.

Minor Changes

• Move AgentType constructor parameters docs to class docstring so it is rendered by Sphinx.
• Remove uses of deprecated time.clock #887
• Change internal representation of parameters to Distributions to ndarray type
• Rename IncomeDstn to IncShkDstn
• AgentType simulate() method now returns history. #916
• Rename DiscreteDistribution.drawDiscrete() to draw()
• Update documentation and warnings around IncShkDstn #955
• Adds csv files to MANIFEST.in. 957

0.10.8

Release Date: Nov. 05 2020

Major Changes

• Namespace variables for the Market class #765
• We now have a Numba based implementation of PerfForesightConsumerType model available as PerfForesightConsumerTypeFast #774
• Namespace for exogenous shocks #803
• Namespace for controls #855
• State and poststate attributes replaced with state_now and state_prev namespaces #836

Minor Changes

• Use shock_history namespace for pre-evaluated shock history #812
• Fixes seed of PrefShkDstn on initialization and add tests for simulation output
• Reformat code style using black

0.10.7

0.10.7

Release Date: 08-08-2020

Major Changes

• Add a custom KrusellSmith Model #762
• Simulations now uses a dictionary history to store state history instead of _hist attributes #674
• Removed time flipping and time flow state, "forward/backward time" through data access #570
• Simulation draw methods are now individual distributions like Uniform, Lognormal, Weibull #624

Minor Changes

• unpackcFunc is deprecated, use unpack(parameter) to unpack a parameter after solving the model #784
• Remove deprecated Solution Class, use HARKObject across the codebase #772
• Add option to find crossing points in the envelope step of DCEGM algorithm #758
• Fix reset bug in the behaviour of AgentType.resetRNG(), implemented individual resetRNG methods for AgentTypes #757
• Seeds are set at initialisation of a distribution object rather than draw method #691 #750, #729
• Deal with portfolio share of 'bad' assets #749
• Fix bug in make_figs utilities function #755
• Fix typo bug in Perfect Foresight Model solver #743
• Add initial support for logging in ConsIndShockModel #714
• Speed up simulation in AggShockMarkovConsumerType #702
• Fix logic bug in DiscreteDistribution draw method #715
• Implemented distributeParams to distributes heterogeneous values of one parameter to a set of agents #692
• NelderMead is now part of estimation #693
• Fix typo bug in parallel #682
• Fix DiscreteDstn to make it work with multivariate distributions #646
• BayerLuetticke removed from HARK, is now a REMARK #603
• cstwMPC removed from HARK, is now a REMARK #666
• SolvingMicroDSOPs removed from HARK, is now a REMARK #651
• constructLogNormalIncomeProcess is now a method of IndShockConsumerType #661
• Discretize continuous distributions #657
• Data used in cstwMPC is now in HARK.datasets #622
• Refactor checkConditions by adding a checkCondition method instead of writing custom checks for each condition #568
• Examples update #768, #759, #756, #727, #698, #697, #561, #654, #633, #775

0.10.6

0.10.6

Release Date: 17-04-2020

Major Changes

• Add Bellman equations for cyclical model example #600

• read_shocks now reads mortality as well #613

• Discrete probability distributions are now classes #610

Minor Changes

0.10.5

0.10.5

Release Date: 24-03-2020

Major Changes

• Default parameters dictionaries for ConsumptionSaving models have been moved from ConsumerParameters to nearby the classes that use them. #527

• Improvements and cleanup of ConsPortfolioModel, and adding the ability to specify an age-varying list of RiskyAvg and RiskyStd. #577

• Rewrite and simplification of ConsPortfolioModel solver. #594

Minor Changes

0.10.4

0.10.4

Release Date: 05-03-2020

Major Changes

• Last release to support Python 2.7, future releases of econ-ark will support Python 3.6+ #478
• Move non-reusable model code to examples directory, BayerLuetticke, FashionVictim now in examples instead of in HARK code #442
• Load default parameters for ConsumptionSaving models #466
• Improved implementaion of parallelNelderMead #300

Minor Changes

• Notebook utility functions for determining platform, GUI, latex (installation) are available in HARK.utilities #512
• Few DemARKs moved to examples #472
• MaxKinks available in ConsumerParameters again #486