# Release Notes#

## Introduction#

This document contains the release notes of HARK. HARK aims to produce an open source repository of highly modular, easily interoperable code for solving, simulating, and estimating dynamic economic models with heterogeneous agents.

For more information on HARK, see our Github organization.

## Changes#

### 0.16.0 (in development)#

Release Date: TBD

### Major Changes#

Adds a discretize method to DBlocks and RBlocks (#1460)[https://github.com/econ-ark/HARK/pull/1460]

Allows structural equations in model files to be provided in string form #1427

Introduces `HARK.parser’ module for parsing configuration files into models #1427

Allows construction of shocks with arguments based on mathematical expressions #1464

YAML configuration file for the normalized consumption and portolio choice #1465

#### Minor Changes#

Fixes bug in

`AgentPopulation`

that caused discretization of distributions to not work. 1275Adds support for distributions, booleans, and callables as parameters in the

`Parameters`

class. 1387Removes a specific way of accounting for ``employment’’ in the idiosyncratic-shocks income process. 1473

Changes the behavior of make_lognormal_RiskyDstn so that the standard deviation represents the standard deviation of log(returns)

Adds detailed parameter and latex documentation to most models.

Add PermGroFac constructor that explicitly combines idiosyncratic and aggregate sources of growth. 1489

### 0.15.1#

Release Date: June 15, 2024

This minor release was produced prior to CEF 2024 to enable public usage of HARK with the SSJ toolkit.

#### Major Changes#

none

#### Minor Changes#

### 0.15.0#

Release Date: June 4, 2024

Note: Due to major changes on this release, you may need to adjust how AgentTypes are instantiated in your projects using HARK. If you are manually constructing “complicated” objects like MrkvArray, they should be assigned to your instances *after* initialization, not passed as part of the parameter dictionary. See also the new constructor methodology for how to pass parameters for such constructed inputs.

This release drops support for Python 3.8 and 3.9, consistent with SPEC 0, and adds support for Python 3.11 and 3.12. We expect that all HARK features still work with the older versions, but they are no longer part of our testing regimen.

#### Major Changes#

Drop official support for Python 3.8 and 3.9, add support for 3.11 and 3.12. #1415

Replace object-oriented solvers with single function versions. #1394

Object-oriented solver code has been moved to /HARK/ConsumptionSaving/LegacyOOsolvers.py, for legacy support of downstream projects.

AgentTypeMonteCarloSimulator now requires model shock, parameter, and dynamics information to be organized into ‘blocks’. The DBlock object is introduced. #1411

RBlock object allows for recursive composition of DBlocks in models, as demonstrated by the AgentTypeMonteCarloSimulator #1417

Transtion, reward, state-rule value function, decision value function, and arrival value function added to DBlock #1417

All methods that construct inputs for solvers are now functions that are specified in the dictionary attribute

`constructors`

. #1410Such constructed inputs can use alternate parameterizations / formats by changing the

`constructor`

function and providing its arguments in`parameters`

.Move

`HARK.datasets`

to`HARK.Calibration`

for better organization of data and calibration tools. #1430

#### Minor Changes#

Add option to pass pre-built grid to

`LinearFast`

. 1388Moves calculation of stable points out of ConsIndShock solver, into method called by post_solve #1349

Adds cubic spline interpolation and value function construction to “warm glow bequest” models.

Fixes cubic spline interpolation for ConsMedShockModel.

Moves computation of “stable points” from inside of ConsIndShock solver to a post-solution method. #1349

Corrects calculation of “human wealth” under risky returns, providing correct limiting linear consumption function. #1403

Removed ‘parameters’ from new block definitions; these are now ‘calibrations’ provided separately.

Create functions for well-known and repeated calculations in single-function solvers. 1395

Re-work WealthPortfolioSolver to use approximate EGM method #1404

Default parameter dictionaries for AgentType subclasses have been “flattened”: all parameters appear in one place for each model, rather than inheriting from parent models’ dictionaries. The only exception is submodels

*within*a file when only 1 or 2 parameters are added or changed. #1425Fix minor bug in

`HARK.distribution.Bernoulli`

to allow conversion into`DiscreteDistributionLabeled`

. #1432

### 0.14.1#

Release date: February 28, 2024

#### Major Changes#

none

#### Minor Changes#

### 0.14.0#

Release Date: February 12, 2024

#### Major Changes#

Adds

`HARK.core.AgentPopulation`

class to represent a population of agents with ex-ante heterogeneous parametrizations as distributions. #1237Adds

`HARK.core.Parameters`

class to represent a collection of time varying and time invariant parameters in a model. #1240Adds

`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,#1253Addresses #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

### 0.13.0#

Release Date: February 16, 2023

#### 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. #1117General control transitions based on decision rules in

`FrameAgentType`

. #1117Adds

`distr_of_function`

tool to calculate the distribution of a function of a discrete random variable. #1144Changes the

`DiscreteDistribution`

class to allow for arbitrary array-valued random variables. #1146Adds

`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. #1107Updates 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`

. #1156Adds

`DiscreteDistributionXRA`

class which extends`DiscreteDistribution`

to allow for underlying data to be stored in a`xarray.DataArray`

object. #1156Adds keyword argument

`labels`

to`expected()`

when using`DiscreteDistributionXRA`

to allow for expressive functions that use labeled xarrays. #1156Adds a wrapper for

`interpolation.py`

for fast multilinear interpolation. #1151Adds support for the calculation of dreivatives in the

`interpolation.py`

wrappers. #1157Adds class

`DecayInterp`

to`econforgeinterp.py`

. It implements interpolators that “decay” to some limiting function when extrapolating. #1165Add 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. #1181Adds Methods to calculate Heterogenous Agent Jacobian matrices. #1185

Enhances

`combine_indep_dstns`

to work with labeled distributions (`DiscreteDistributionLabeled`

). #1191Updates the

`numpy`

random generator from`RandomState`

to`Generator`

. #1193Turns the income and income+return distributions into

`DiscreteDistributionLabeled`

objects. #1189Creates

`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`

. #1168Reorganizes

`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, #1115Allows 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. #1131Fixes scaling bug in Normal equiprobable approximation method. 1139

Removes the extra-dimension that was returned by

`calc_expectations`

in some instances. #1149Adds

`HARK.distribution.expected`

alias for`DiscreteDistribution.expected`

. #1156Renames 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`

. #1172Renames

`DiscreteDistributionXRA`

to`DiscreteDistributionLabeled`

and updates methods #1170Renames

`HARK.numba`

to`HARK.numba_tools`

#1183Adds the RNG seed as a property of

`DiscreteDistributionLabeled`

#1184Updates the

`approx`

method of`HARK.distributions.Uniform`

to include the endpoints of the distribution with infinitesimally small (zero) probability mass. #1180Refactors tests to incorporate custom precision

`HARK_PRECISION = 4`

. #1193Cast

`DiscreteDistribution.pmv`

attribute as a`np.ndarray`

. #1199Update structure of dynamic interest rate. #1221

### 0.12.0#

Release Date: December 14, 2021

#### Major Changes#

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 #1057Use

`np.fill(np.nan)`

to clear or initialize the arrays that store simulations. #1068Add 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`

#1047Update

`ConsGenIncProcessModel.py`

to use`calc_expectation`

method #1072Fix bug in

`calc_normal_style_pars_from_lognormal_pars`

due to math error. #1076Fix bug in

`distribute_params`

so that`AgentCount`

parameter is updated. #1089Fix bug in ‘vFuncBool’ option for ‘MarkovConsumerType’ so that the value function may now be calculated. #1095

### 0.11.0#

Release Date: 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/econ-ark/HARK/pull/897/)

Implements the multivariate normal as a supported distribution, with a discretization method. See #948.

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 #903Adds 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 #947Moves 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#

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 #674Removed 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#

Release Date: 17-04-2020

#### Major Changes#

#### Minor Changes#

### 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#

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#

### 0.10.3#

Release Date: 12-12-2019

#### Major Changes#

Added constrained perfect foresight model solution. (#299

#### Minor Changes#

Fixed slicing error in minimizeNelderMead. (#460)

Fixed matplotlib GUI error. (#444)

Pinned sphinx dependency. (#436)

Fixed bug in ConsPortfolioModel in which the same risky rate of return would be drawn over and over. (#433)

Fixed sphinx dependency errors. (#411)

Refactored simultation.py. (#408)

AgentType.simulate() now throws informative errors if attributes required for simulation do not exist, or initializeSim() has never been called. (#320)

### 0.10.2#

Release Date: 10-03-2019

#### Minor Changes#

### 0.10.1.dev5#

Release Date: 09-25-2019

#### Minor Changes#

Added portfolio choice between risky and safe assets (ConsPortfolioModel). (#241)

### 0.10.1.dev4#

Release Date: 09-19-2019

#### Minor Changes#

### 0.10.1.dev3#

Release Date: 07-23-2019

#### Minor Changes#

### 0.10.1.dev2#

Release Date: 07-22-2019

#### Minor Changes#

Revert pre-solve commit due to bug. (#363)

### 0.10.1.dev1#

Release Date: 07-20-2019

#### Breaking Changes#

See #302 under minor changes.

#### Major Changes#

Adds BayerLuetticke notebooks and functionality. (#328)

#### Minor Changes#

Fixes one-asset HANK models for endowment economy (had MP wired in as the shock). (#355)

Removes jupytext *.py files. (#354)

Reorganizes documentation and configures it to work with Read the Docs. (#353)

Adds notebook illustrating dimensionality reduction in Bayer and Luetticke. (#345)

Adds notebook illustrating how the Bayer & Luetticke invoke the discrete cosine transformation(DCT) and fixed copula to reduce dimensions of the problem.(#344)

Makes BayerLuetticke HANK tools importable as a module. (#342)

Restores functionality of SGU_solver. (#341)

Fixes datafile packaging issue. (#332)

Deletes .py file from Bayer-Luetticke folder. (#329)

Add an empty method for preSolve called checkRestrictions that can be overwritten in classes inheriting from AgentType to check for illegal parameter values. (#324)

Adds a call to updateIncomeProcess() in preSolve() to avoid solutions being based on wrong income process specifications if some parameters change between two solve() calls. (#323)

Makes checkConditions() less verbose when the checks are not actually performed by converting a print statement to an inline comment. (#321)

Raises more readable exception when simultate() is called without solving first. (#315)

Removes testing folder (part of ongoing test restructuring). (#304)

Fixes unintended behavior in default simDeath(). Previously, all agents would die off in the first period, but they were meant to always survive. (#302)

**Warning**: Potentially breaking change.

### 0.10.1#

Release Date: 05-30-2019

No changes from 0.10.0.dev3.

### 0.10.0.dev3#

Release Date: 05-18-2019

#### Major Changes#

Fixes multithreading problems by using Parallels(backend=’multiprocessing’). (287)

Fixes bug caused by misapplication of check_conditions. (284)

Adds functions to calculate quadrature nodes and weights for numerically evaluating expectations in the presence of (log-)normally distributed random variables. (258)

#### Minor Changes#

Adds method decorator which validates that arguments passed in are not empty. (282

Lints a variety of files. These PRs include some additional/related minor changes, like replacing an exec function, removing some lambdas, adding some files to .gitignore, etc. (274, 276, 277, 278, 281)

Adds vim swp files to gitignore. (269)

Adds version dunder in init. (265)

Adds flake8 to requirements.txt and config. (261)

Adds some unit tests for IndShockConsumerType. (256)

### 0.10.0.dev2#

Release Date: 04-18-2019

#### Major Changes#

None

#### Minor Changes#

Fix verbosity check in ConsIndShockModel. (250)

#### Other Changes#

None

### 0.10.0.dev1#

Release Date: 04-12-2019

#### Major Changes#

Adds tools to solve problems that arise from the interaction of discrete and continuous variables, using the DCEGM method of Iskhakov et al., who apply the their discrete-continuous solution algorithm to the problem of optimal endogenous retirement; their results are replicated using our new tool here. (226)

Parameters of ConsAggShockModel.CobbDouglasEconomy.updateAFunc and ConsAggShockModel.CobbDouglasMarkovEconomy.updateAFunc that govern damping and the number of discarded ‘burn-in’ periods were previously hardcoded, now proper instance-level parameters. (244)

Improve accuracy and performance of functions for evaluating the integrated value function and conditional choice probabilities for models with extreme value type I taste shocks. (242)

Add calcLogSum, calcChoiceProbs, calcLogSumChoiceProbs to HARK.interpolation. (209, 217)

Create tool to produce an example “template” of a REMARK based on SolvingMicroDSOPs. (176)

#### Minor Changes#

Moved old utilities tests. (245)

Deleted old files related to “cstwMPCold”. (239)

Set numpy floating point error level to ignore. (238)

Improve the tests of buffer stock model impatience conditions in IndShockConsumerType. (219)

Add basic support for Travis continuous integration testing. (208)

Add SciPy to requirements.txt. (207)

Fix indexing bug in bilinear interpolation. (194)

Update the build process to handle Python 2 and 3 compatibility. (172)

Add MPCnow attribute to ConsGenIncProcessModel. (170)

All standalone demo files have been removed. The content that was in these files can now be found in similarly named Jupyter notebooks in the DEMARK repository. Some of these notebooks are also linked from econ-ark.org. (229, 243)

#### Other Notes#

Not all changes from 0.9.1 may be listed in these release notes. If you are having trouble addressing a breaking change, please reach out to us.