U Kv fã8ã @s2dZddlmZddlZddlmZdgZddlm Z dd„Z d d „Z Gd d „d e ƒZ Gd d„dƒZ Gdd„de ƒZGdd„de ƒZGdd„de ƒZedkr.ddlmmZddlZddlm Z ddlmZejj ¡Zejdd…Zejdd…Zej edee!ddZ"e #e"¡Z$e$ %ddg¡ &¡Z'eddg (e!¡ )dd¡Zej*eddZe edƒZ+edZ,e eee+e,ddgd d!Z-e-j.d"d#Z/e-j.d$d%d&Z0e-j.d'd%d&Z1e-j.d$d(d&Z2e-j.d'd(d&Z3e-j.d'd)d&Z4e 5dddd*d*dddg¡Z6e6j7dZ8e 9e6¡Z:e 5dd*dd*ddd*dg¡Z;e 9e;¡Ze;dd…dfeeCe?fZEe FeEeEjG¡e@e He8¡ZIeJeIƒeJejK LeI¡ƒejK MeI¡\ZNZOe FeOd*eNeOjG¡ZPejK QeI¡ZRe FeOeNeOjG¡ZSeJe Te UeSeI¡¡ƒeJe Te Ue FePeI¡e He8¡¡¡ƒeOe AeN¡ZVeJe Te Ue FeVeVjG¡eP¡¡ƒe 5eBeCe@g¡ZWe Xe6e;f¡ZYe eYeWƒ\ZZZ[Z\eJe Te UeZeI¡¡ƒeJe Te Ue[eP¡¡ƒeJe Te Ue\eV¡¡ƒeejFe>ejK Qe Fe>jGe>¡¡e>jGgƒZ]e He8¡e]Z^eJe Te Ue Fe^e6¡¡¡ƒdS).z Sandbox Panel Estimators References ----------- Baltagi, Badi H. `Econometric Analysis of Panel Data.` 4th ed. Wiley, 2008. é)ÚreduceN)ÚGLSÚ PanelModel)ÚPanelcCsZi}t t|ƒ¡}tt|ƒƒD]6}|||krD| ||t|ƒi¡|||||<q|S)zÓ Returns unique numeric values for groups without sorting. Examples -------- >>> X = np.array(['a','a','b','c','b','c']) >>> group(X) >>> g array([ 0., 0., 1., 2., 1., 2.]) )ÚnpÚzerosÚlenÚrangeÚupdate)ÚXZ uniq_dictÚgroupÚi©rúF/tmp/pip-unpacked-wheel-2v6byqio/statsmodels/sandbox/panel/panelmod.pyr s  r c CsÌ|jdkr|dd…df}|j\}}|dt |¡}t|ƒD]N}|dd…||d…f}t |¡}||||k t¡}|t ||j ¡7}q>tj   |¡\} } t | d| | j ¡} | t  | ¡} || | fS)aGcalculate error covariance matrix for random effects model Parameters ---------- groups : ndarray, (nobs, nre) or (nobs,) array of group/category observations sigma : ndarray, (nre+1,) array of standard deviations of random effects, last element is the standard deviation of the idiosyncratic error Returns ------- omega : ndarray, (nobs, nobs) covariance matrix of error omegainv : ndarray, (nobs, nobs) inverse covariance matrix of error omegainvsqrt : ndarray, (nobs, nobs) squareroot inverse covariance matrix of error such that omega = omegainvsqrt * omegainvsqrt.T Notes ----- This does not use sparse matrices and constructs nobs by nobs matrices. Also, omegainvsqrt is not sparse, i.e. elements are non-zero éNéÿÿÿÿ) ÚndimÚshaperÚeyer ÚuniqueÚastypeÚfloatÚdotÚTÚlinalgÚeighÚsqrt) ÚgroupsZsigmasÚnobsZnreÚomegaZigrr Ú groupuniqÚdummygrÚevÚevecÚomegainvÚ omegainvhalfrrrÚ repanel_cov's    r&c@s eZdZdS)Ú PanelDataN©Ú__name__Ú __module__Ú __qualname__rrrrr'Ssr'c@sNeZdZdZddd„Zdd„Zdd„Zdd d „Zdd d„Zdd„Z dd„Z dS)raà An abstract statistical model class for panel (longitudinal) datasets. Parameters ---------- endog : array_like or str If a pandas object is used then endog should be the name of the endogenous variable as a string. # exog # panel_arr # time_arr panel_data : pandas.Panel object Notes ----- If a pandas object is supplied it is assumed that the major_axis is time and that the minor_axis has the panel variable. NcCs |dkr| ||||||¡dS©N)Ú initialize)ÚselfÚendogÚexogÚpanelÚtimeÚxtnamesÚequationÚ panel_datarrrÚ__init__iszPanelModel.__init__c CsÎ| d¡}|d|_|dd…}|d|_|d|_| d¡dk} d| krlt | dk¡dd} | | d¡| |_||_ t  t  |¡¡|_ t  |¡}||_ t  |¡|_t  |¡|_t |¡|_t |¡|_dS)zG Initialize plain array model. See PanelModel ú rrNTZcons)ÚsplitÚ endog_nameZ panel_nameZ time_nameÚvarrÚwhereÚinsertÚ _cons_indexÚ exog_namesÚsqueezeZasarrayr/r0r1r2rÚ paneluniqÚtimeuniq) r.r/r0r1r2r3r4Únamesr>ZnovarZ cons_indexrrrr-zs$          zPanelModel.initializecCsf||_||j}t |¡|_|dkr8|j ¡}| |¡| |¡j|_ ||_ ||_ |j |_ |j|_dSr,)r5Úvaluesrr?r/ÚcolumnsÚtolistÚremoveZ filterItemsr0Z _exog_nameZ _endog_nameZ major_axisZ _timeseriesZ minor_axisZ _panelseries)r.r5r9Z exog_namer/rrrÚinitialize_pandas¸s    zPanelModel.initialize_pandasÚonewayFc CsH|dkr|j}|j}n"|dkr,|j}|j}n td|ƒ‚t|||dd…dft|ƒt|ƒt|dd…dfƒ|ƒ||dd…dfk t¡}|j dkr¸t   ||¡|  d¡dd…df}nt   ||¡|  d¡}|dkrâ|dkrâ|S|dkr|dkr||  d¡fS|dkr(|dkr(||  d¡|fS|dkrD|dkrD||fSdS)z[ Get group means of X by time or by panel. index default is panel rHr2zindex %s not understoodNrFT) r1r@r2rAÚ ValueErrorÚprintrrrrrrÚsum) r.r ÚindexÚcountsÚdummiesÚYZuniqÚdummyZmeanrrrÚ _group_meanÈs, 2ÿ $zPanelModel._group_meancCsr|r | ¡}| ¡}|r,|dkr,td|ƒ‚|dkrFt|j|jƒ ¡S|dkrZ| ||¡S|dkrn| ||¡SdS)ab method : LSDV, demeaned, MLE, GLS, BE, FE, optional model : between fixed random pooled [gmm] effects : oneway time twoway femethod : demeaned (only one implemented) WLS remethod : swar - amemiya nerlove walhus Notes ----- This is unfinished. None of the method arguments work yet. Only oneway effects should work. )ZlsdvZdemeanedZmleZglsÚbeZfez%s not a valid methodÚpooledÚbetweenÚfixedN)ÚlowerrIrr/r0ÚfitÚ _fit_btwnÚ _fit_fixed)r.ÚmodelÚmethodÚeffectsrrrrWès   zPanelModel.fitcCsH|dkr*|j|j|d}|j|j|d}n td|ƒ‚t||ƒ ¡}|S)NZtwoway©rLz1%s effects is not valid for the between estimator)rQr/r0rIrrW)r.r[r\r/r0ZbefitrrrrXsÿzPanelModel._fit_btwnc Csê|j}|j}d}|dkrx|dkr(d}d}|j||dd\}}|j||d}| t¡}|t ||¡}|tj||dd }|s„|d krÈ|j|d dd \}} |j|d d}|t || ¡}|t | j|¡}t ||dd…|j fƒ  ¡} | S) NF)rHÚtwowaysr^TrH)rLrMr]r)Zaxisr2)rLrN) r/r0rQrÚintrÚrepeatrrrr=rW) r.r[r\r/r0Z demeantwiceZ endog_meanrMZ exog_meanrNZfefitrrrrY)s.ÿ   ÿ zPanelModel._fit_fixed)NNNNNNN)rHFF)NNrH) r)r*r+Ú__doc__r6r-rGrQrWrXrYrrrrrVsÿ > 6 c@s eZdZdS)ÚSURPanelNr(rrrrrbEsrbc@s eZdZdS)ÚSEMPanelNr(rrrrrcHsrcc@s eZdZdS)Ú DynamicPanelNr(rrrrrdKsrdÚ__main__iìÿÿÿZ investmentF)ZusemaskÚyearZfirmÚvalueZcapitalré)Úprependzinvest value capital)r3r4rS)rZrTrH)rZr\rUr2r^rgð?g@g@)_raÚ functoolsrZnumpyrZ#statsmodels.regression.linear_modelrÚ__all__Zpandasrr r&r'rrbrcrdr)Znumpy.lib.recfunctionsÚlibZ recfunctionsZnprfZstatsmodels.apiÚapiÚsmZdatasetsZgrunfeldÚloadÚdatar/r0ZfullexogZ append_fieldsrZ panel_arrZ DataFrameZpanel_dfZ set_indexZto_panelZ panel_pandaÚviewZreshapeZ add_constantr1rfZ panel_modrWZ panel_olsZpanel_beZpanel_feZ panel_betZ panel_fetZ panel_fe2Úarrayrrrrr ZperiodsZ perioduniqrr!ZdummypeÚsigmarZsigmagrZsigmapeZc_ZdummyallrrrrrJrZcholeskyrr"r#r$ÚinvZ omegainv2Z omegacompÚmaxÚabsr%Zsigmas2Z column_stackZgroups2Zomega_Z omegainv_Z omegainvhalf_ZPgrZQgrrrrrÚs’   ,p     ÿ  ÿ       &" ÿ