Maddala, G. S., 1984, Limited-dependent and qualitative variables in econometrics. Cambridge: Cambridge University Press.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....will contain a larger proportion of the more frequent low amount donors) our estimates will be biased low for individuals who have a low donation probability. Survey nonresponse is an actively researched field of study [Little, 1985, Hall, Heckman, 1976, Little, 1982, Little and Rubin, 1986, Maddala, 1983] In [Little, 1985] the authors point out the two major approaches to the study of survey nonresponse, namely the randomization and the model based approaches. Randomization inference considers the population of all possible responses and a sampling distribution on top of it. The samples are ....

Maddala, G. S. (1983). Limited-dependent and qualitative variables in econometrics. Cambridge University Press.

....these variables cannot be simply used to predict the village level poverty incidence. Using Taylor expansions, it is nevertheless possible to obtain an approximation. For this purpose, 4) can be expanded around ( b V j X s j ) Using the property that E(b X ij b V j X ) 0, we obtain (Maddala (1983)) E(H ) E(F ( b X ij s j ) F( b V j X s j ) b V X s j 3 ) f( b V j X s j ) E(b X ij b V j X ) 2 (5) where f( is the normal density function and E(b X ij b V X ) 2 is the variance of the predicted household level consumption around the predicted mean ....

....for situations in which the observed data were dichotomous or truncated at zero. The standard way of writing the solution to this estimation problem is then to define a regression model in which a continuous latent (unobserved) variable is regressed on a set of observed explanatory variables (Maddala (1983)) A particular error structure (e.g. the normal distribution for the probit) is then assumed, allowing the parameters of inference to be estimated. These village and the village level variance of the prediction model. 8 Hentschel et al. 1998) use this property to predict regional poverty from ....

Maddala, G. S., (1983), Limited dependent and qualitative variables in econometrics, Cambridge University Press.

....we could model the process with a binomial distribution. The binomial assumption and Equation (4) then set up a standard grouped logit model that we could estimate either via maximum likelihood (as in King and Browning 1987) or two step minimum Chi Square methods (see Greene 1993:653 657 or Maddala 1983:28 34) However, we suspect that there is still some unmodeled heterogeneity beyond that being picked up by the logistic of the vote shares and possibly some correlation in the probabilities across districts. In fact, an optimal partisan gerrymander would require such heterogeneity ....

Maddala, G.S. 1983. Limited Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.

....structure of the decomposition described in the next section makes it very difficult to use a nonlinear method of estimating the probability of attending private school. Although it is well known that OLS provides consistent parameter estimates when using a discrete dependent variable (see Maddala [13] for example) the fact that the predicted probabilities can lie outside the range of 0 to 1 can be a concern. Therefore, we compare our coefficient estimates to the average derivatives from a probit model. A simple regression of the OLS coefficient estimates on the probit average derivatives ....

G.S. Maddala, "Limited-Dependent and Qualitative Variables in Econometrics" Cambridge University Press, Cambridge, UK (1983).

....eqn. 9) and (10) There are two ways to deal with this. One is to correct for sample selection using, for example, Heckman s twostep procedure with a sample selection equation (Greene, 1990) Alternatively, we can apply a Tobit procedure, recognizing that acreage and output are truncated at zero (Maddala, 1983). Either method will have problems when spatial autocorrelation exists in the data (which is likely here) but these problems have substantially less effect for the first method, which we follow here. 10 To be more specific, we correct our estimation for spatial and temporal autocorrelation, ....

Maddala, G.S., Limited-Dependent and Qualitative Variables in Econometrics (Cambridge University Press, Cambridge, UK, 1983).

....0 #; #21# 16 For the problem studied in this paper, the Bivariate Probit model speci#es Y =1f# 0 # D X 0 # 0 ,U Y # 0g and D =1f# 0 # Z X 0 # 0 , UD # 0g,where1fAg denotes the indicator function for the event A and the error terms U Y and UD have a joint normal distribution. See Maddala #1983#, p.122 for details. 29 where # 0 = # #=#, # 0 = #=# U , # 0 = ## U =# , 1# and # = q # 2 U # 2 # . Column #9# is based on least squares estimation of the model in equation #21#. Under misspeci#cation of the random coe#cients model, the estimates in column #9# can still be ....

Maddala, G. S. #1983#,Limited-Dependent and Qualitative Variables in Econometrics. Econometric Society Monograph No. 3. Cambridge: Cambridge University Press.

....in#uenced candidate choices and that candidate choice in#uenced voter support for or opposition to the initiative. As is true of the linear regression model, endogeneity in binary choice models results in biased coe#cients and, therefore, incorrect inferences #Alvarez, 1997; Amemiya, 1978; Maddala, 1983; Rivers and Vuong, 1988#. Our expectations about endogeneity lead us to posit the following structural model for these underlying predispositions: Y P187 = X i1 # 1 # 1G YGR # 1S YSR 1 #3# 7 YGR = X i2 # 2 # 2P Y P187 2 YSR = X i3 # 3 # 3P Y P187 3 where Y P187 is the ....

....b Y P187 , b YGR , and b YSR #. Next, these predicted values are substituted for the right hand side endogenous variables of Equation 3, and then we estimate the model also using probit. This two stage procedure yields consistent estimates of the model parameters in Equation 3 #Amemyia, 1978; Maddala, 1983; Rivers and Vuong, 1988# and has been used in political science research #Alvarez, 1997; Fiorina, 1981; Franklin and Jackson, 1983#. Given this estimation procedure for the model, we now consider the model speci#cation. We discuss howwe specify the independentvariables for the Proposition 187 ....

Maddala, G. S. 1983. Limited-Dependent and Qualitative Variables in Econometrics. Econometric Society Monographs, No. 3. Cambridge: Cambridge University Press.

....P and # H, and # Di and # Ri are random variables, independentof # P and # H , with a joint GEV distribution Pr## Di #V D ;# Ri #V R # = expf,G#e ,VD ;e ,VR #g where G#e ,VD ;e ,VR #=#e ,VD =1,# e ,VR =1,# # 1,# for constant #,0# ##1. If # = 0 then # Di and # Ri are independent #Maddala 1983, 70#72#. The assumed forms give # i = # P = c Pi c PRi # Ri c PDi # Di # i = # H = c Hi c HRi # Ri c HDi # Di where the nonrandom coe#cients, functions of # P and # H, are c Pi = # # P# Ri #1, # P ## Di #= # P , c PRi = # P# Ri = # P , c PDi = #1 , # P ## ....

Maddala, G. S. 1983. Limited-dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.

....MNP and MNL models we refer the reader to any of the several good, general discussions of these models #Alvarez and Nagler, 1995; Lawrence, 1997; Alvarez and Nagler, 1998# aimed at a political science audience. These papers also discuss various classical estimation strategies, as do the works of Maddala #1983# and Greene #1997#. 3.1 Random Utility Motivation 12 Given data from n individuals #voters# choosing between p alternatives #parties# both the MNP model and the MNL model can be motivated by the following random utility model: z i = V i # W i # u i #1# y ij = # 1ifz ij = max#z i # 0 ....

Maddala, G. S. 1983. Limited-dependent and Qualitative Variables in Econometrics . Cambridge: Cambridge University Press.

....is that the probability of choice at each stage is independent of the probability of the choice at other 16 The specialist was not obligated to include SuperDOT limit orders in his quotes up until March 30, 1993. But he still can choose how much size to display at the quotes. 23 stages (see Maddala (1983)) However, the actual sequence used for estimation could be one of several possible sequences including a reverse of what is being used, making them fairly robust to the choice of sequence. All these models are estimated individually for stocks eliminating the need to control for differences ....

Maddala, G. S., 1983, Limited Dependent and Qualitative Variables in Econometrics (Cambridge University Press, Cambridge).

....as in many recent studies of provider choice, we estimate the choice probabilities as nested multinomial logits. This is a generalization of the multinomial logit model that allows error terms to be correlated across alternatives within a subgroup of related choices but not across subgroups (Maddala 1983). 95 Following standard practice we assume that the error terms of the schooling choices, which in the present case consist of public school and private school, are correlated. Letting K=3 be the total number of alternatives and numbering them 1 for nonenrollment, 2 for public school, and 3 for ....

Maddala, G.S. 1983. "Limited Dependent and Qualitative Variables in Econometrics." Econometric Society Monograph No. 3, Cambridge University Press, Cambridge.

....an additional parameter to be estimated 7 , so that we have the formulation in inequality #2# but without any restriction on the values that # p can take on, instead we estimate not only the examinee parameter # v , but also the question parameters # p and # p . In other words, we do not need 6 Maddala #1986#. 7 Birnbaum #1968#. 4 to know a priori which are the correct answers to the questions Our estimates of # p will tell us which answers are correct 8 . If we knew the examinees ability parameters, the # v , then estimating the # p and # p parameters would be straightforward. The ....

Maddala, G. S. #1986# Limited Dependent and Qualitative Variables in Econometrics #New York: Cambridge University Press#.

....(1996) as a stochastic actor oriented model. The evaluation includes a random element to account for the deviation between theoretical expectation and observed reality, which leads to a kind of random utility model (cf. random utility models commonly used in econometrics and treated, e.g. in Maddala, 1983). The models can be implemented as stochastic simulation models, which is the basis for the MCMC procedure for parameter estimation. This is a frequentist procedure, using the method of moments. The MCMC implementation of the method of moments uses a stochastic approximation algorithm which is a ....

....Given that actor i may change an outgoing relation, he chooses to change his relation to that actor j (j #= i) for whom the value of (4) is highest. It is convenient to let the U i (t, x, j) have the type 1 extreme value distribution (or Gumbel distribution) with mean 0 and scale parameter 1 (Maddala, 1983). This assumption is commonly made in random utility modeling in econometrics. When this distribution is used, the probability that the given actor i chooses the other actor j for changing the relation x ij , is the multinomial logit expression, cf. Maddala (1983, p. 60) p ij (#, x) exp(f i ....

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Maddala, G.S. 1983. Limited-dependent and qualitative variables in econometrics. Cambridge: Cambridge University Press.

....correlated with E , 1 2 resulting in simultaneity bias. When the outcome variable is continuous and observable (for example, household caloric intake, total food expenditures, anthropometric measures) a twostage procedure may be used to produce unbiased and consistent estimates of program impact (Maddala 1983). When access to a special credit program is being analyzed, A in equation (6) may be a binary variable indicating membership of a special credit program. The specification may be the following: 57 A z E , 8) 1 1 1 where A is a continuous but latent variable describing access ....

.... by probit 1 1 maximum likelihood method for equation (8) As for equation (7) it can be rewritten as Y = z ( M M( z ) w, 9) 1 2 2 1 1 where M M is the cumulative distribution function of a standard normal distribution, and w has a zero mean and is uncorrelated with the regressors (Maddala 1983). Equation (9) can now be estimated by OLS after substituting with # . Note that, unlike in 1 1 the case of the usual simultaneous equations models, equation (9) can be estimated even if z contains all variables in z . This is because A is replaced by a nonlinear 2 1 function, M M(# z ) and ....

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Maddala, G. 1983. Limited dependent and qualitative variables in econometrics.

....likelihood ratio index has been calculated for each probit equation. The likelihood ratio index ranges from 0 to 1 and can be interpreted in a similar manner to the R 2 statistic reported in ordinary least squares regressions. For a more technical discussion of the likelihood ratio index see Maddala (1983). Probit Results: Life Insurers This section reports results for individual life health insurance companies, i.e. each company is treated as a separate observation unit whether or not it is a member of a group. To 25 control for group affiliation, we include a dummy variable equal to 1 if the ....

Maddala, G. S., 1983, Limited-Dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.

.... models of the household and models of marital formation also suggests that individual unearned incomes and I (i k J 0i X i J 1i ZJ 2i e i , I ( ik 1 27 See, for example, Manser and Brown (1981) McElroy (1990) and McElroy and 11 Horney (1981) See Heckman (1983) and Maddala (1983). 12 (5) spouse s characteristics affect time allocation decisions. Community characteristics 11 such as household proximity to services, presence of factories or small scale industries, and characteristics of the agricultural production environment such as irrigation and seasonality also ....

Maddala, G. S. 1983. Limited-dependent and qualitative variables in econometrics.

....identify the effect of unobserved productivity in nonfarm and livestock activities on crop output, after correction for the fact that labor is a censored variable. The approach is similar in spirit to the use of the inverse Mills ratio to control for self selection bias (for example, Heckman 1976; Maddala 1983), except that the selection equation is a tobit, not a probit. This parallels work by Pitt, Rosenzweig, and Hassan (1990) who use residuals from a health production function in their analysis of intrahousehold food distribution, and Behrman, Birdsall, and Deolalikar (1995) in their analysis of ....

....that activity will differ from that of how much labor to allocate to it conditional on having undertaken it. We therefore estimate the labor use equation separately from the decision to undertake a particular activity. We apply the two step Heckman estimator used for selection models (see Maddala 1983; Greene 1997 for details) Year and village fixed 21 effects are included but not shown. Family background variables father s landholdings, inherited land, and father s and mother s education are used as identifying restrictions. They are preferable to unearned income since rents, pensions, ....

Maddala, G. S. 1983. Limited dependent and qualitative variables in econometrics.

.... (LNAMT)Z i 1 2 3 (LNAMT)M e , 2) 4 i where DELIQ = 0 if DELIQ # 0 i i and DELIQ = DELIQ if DELIQ 0. i i i In this framework, DELIQ is a latent variable observable only when it takes a i positive value. Equation (2) is estimated by using the TOBIT maximum likelihood technique (Maddala 1983). Since heteroskedasticity results in a highly inconsistent maximum likelihood estimator, the model was tested, and subsequently corrected for 13 heteroskedasticity, based on the method proposed by Greene (1993) The variance of the error term, F , is specified multiplicatively as i F = Fe , i ....

Maddala, G. 1983. Limited dependent and qualitative variables in econometrics.

....# H i;D #= # H i;D =#N # V i;A # gives # # H i;D , # H i;A ### i;D ,# i;A #=# # H i;D , # H i;A #=# # H i;D , # H i;A ### i;A , # i;D #=# # H i;A , # H i;D # #,#N # V i;A # ,1 # H i;D d# i =d # H i . 6. See Mebane #2000# for general motivation for the GEV distribution. Maddala #1983# gives an introductory discussion of GEV choice models. 7. An exact tie between two # i;h values, h 2 K, is a measure zero event that may be ignored. 8. Let f # denote the densityof# ion R 3 #the real line three times#. The basic result is Z Z Z R 3 # # i;h , # # k i ;h #df # ## i #df ....

Maddala, G. S. 1983. Limited-dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.

....without observation of to the latter assignment. The model works excellently for industry bargaining but fails for the other two regimes (no convergence, little gain in log likelihood) For each type of firm bargaining regime we have also estimated a standard endogenous switching regression model (Maddala, 1983, 283) Table 6 gives results for standard switching regression and Table 7 for the extended Dickens Lang model. The extended Dickens Lang model is a relevant extension of the standard switching regression, as judged by the gain in log likelihood. The Dickens Lang identification of regimes is ....

Maddala, G. (1983), Limited-Dependent and Qualitative variables in Econometrics, Cambridge University Press.

.... 0. But if P i;R Gamma P i;D is very small, then ( i;R Gamma i;D ) P i;R Gamma P i;D ) d i =d P i . 5. Strictly speaking, to define P i with reference to the Electoral College, I will assume that the number of voters in each of the M groups in each State is common knowledge. 6. See Maddala 1983 for an introductory discussion of GEV choice models. 7. It is possible to specify GEV distributions in which there is also dependence among all the pairs that include a candidate from one party. That is, ffl RRi , ffl RDi , and ffl DRi are dependent, or ffl RDi , ffl DRi , and ffl DDi are ....

Maddala, G. S. 1983. Limited-dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.

.... j e i max ; fi; oe 2 ) Y i: p i =0 Phi(w 0i =oe) Y i:0 p i h i p i6=i max oe Gamma1 OE(w 1i =oe) Y i: p i =h i p [1 Gamma Phi(w 2i =oe) 11) where OE( Delta) and Phi( Delta) respectively denote the standard normal density and cumulative distribution functions (cf. Maddala 1983, 160) Unknown parameters in (11) are e i max , fi and oe 2 . The likelihood is defined for the case where there is at least one positive contribution that is not equal to h i p. Pooling Multiple PACs To discuss how our model may be used to analyze campaign contributions from multiple PACs, ....

Maddala, G. S. 1983. Limited-dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.

....censored, or two limit, Tobit model. The Tobit model and its maximum likelihood estimation are discussed in the rest of this section. Tobit Models The Tobit model belongs to the class of regression models in which the dependent variable is observed only within a certain range (Tobin, 1958; Maddala, 1983). Consider a latent variable, y i , and suppose only those values of y i that are greater than a known constant, k, are recorded. For values of y i k, the value of k is recorded instead. The observations then are, y i = y i , if y i k = k, otherwise for i = 1, 2, n, ....

Maddala, G.S. (1983) Limited Dependent and Qualitative Variables in Econometrics. Cambridge University Press, Cambridge.

....account though that income itself may be endogenously affected by participation, because income generating activities are a main focus of both projects. We therefore apply a two stage method for mixed qualitative and censored variables, involving a ML estimation by probit in the second stage (see Maddala, 1983). In a first step income is estimated for a reduced form equation 2 , using a tobit regression (see Equation 2) v c Z Z y i hh P P P = 3 2 1 Equation 2 In a second step we estimate the structural equation for participation by incorporating predicted income and by estimating a probit. ....

Maddala, G. S. 1983. "Limited-Dependent and Qualitative Variables in Econometrics." Econometric Society Monographs No. 3, Cambridge University Press: Cambridge.

....one has panel data, selection bias can be controlled for by estimating a fixed effects model. This, however, assumes that the omitted variable that is correlated with program participation is fixed over time. A more general way to control for selection bias, in an evaluation framework, is given by Maddala (1983) who suggests the following model. Model 2 (Two Stage Model) y ci = X ci b c u ci (2) y nci = X nci b nc u nci (3) Ext i = Z i g e , Ext i = 1 iff Ext i 0 and Ext i = 0 iff Ext i 0. 4) Subscript c denotes client observations and nc denotes non client observations. We observe a client ....

....include a dummy, in Z, for whether the plant is in a SMSA that contains a manufacturing extension center. It seems likely that being near a center would affect the likelihood of becoming a client, but not necessarily measures of plant performance such as sales and productivity growth. 11 See Maddala (1983) for a large number of cites in the general applied econometrics literature. Stromsdorfer (1987) and Moffitt (1991) provide reviews of the evaluation literature. This model is more general than (1) in two important ways. First, it allows the coefficients in b to differ for clients and ....

Maddala, G. S., Limited-Dependent and Qualitative Variables in Econometrics, Cambridge University Press, New York, (1983).

.... This involves constructing the likelihood function based on the probabilities defined by Eqs. 2) and (3) and solving for coefficients that yield the highest likelihood that the model generated the data. We used the statistical package LIMDEP (Greene, 1992) Techniques are described in detail in Maddala (1983). 110 D.N. Wear et Ecology and Management 118 (1999) 107 115 variables on probability that land would be commer cial timberland we test the significance of the model as a whole using log likelihood ratio tests and for the significance of coefficients using t statistics. 3.2. Estimating the ....

Maddala, G.S., 1983. Limited Dependent and Qualitative Variables in Econometrics. Cambridge University Press, New York.

....is trichotomous, taking a value of 2 for cases moving off W 2, of 1 for cases moving to a higher tier, and of 0 for those cases remaining in a lower tier. An ordered probit model requires that the dependent variable be ordinal, but not cardinal. For a description of ordered probit models, see Maddala (1983). 32 Our measure of Medicaid participation includes whether anyone in the original W 2 case is participating in any of the Medicaid sub programs, including Healthy Start. To explore the types of cases that are most likely to move up or off W 2, we conducted a multivariate analysis of the cases ....

Maddala , G. S. 1983. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.

....in Appendix C. The parameter vector r r for the reduced form probit equation (6) is estimated using maximum likelihood. We also tested a binary logit model, with similar results. The standard errors in the IV fatality rate regression (7 ) are calculated following the methodology presented in Maddala (1983). The probit equation included the regressors in X A as well as five additional exogenous variables hypothesized to be related to the political sentiment for no fault (see Appendix C) The five variables are the cost of one day of hospitalization, the percentage of state legislators who are ....

Maddala, G.S. (1983). Limited-Dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.

....Another aspect is the good interpretability of the index z T in all fields of applied statistics. Especially the study of marginal effects is an easy task for this structure of the exogeneous covariables. Any generalization should take care of these properties, see Fahrmeir Tutz (1994) Maddala (1983). However, recent studies in econometrics and biology have questioned the strict linear structure of the index or the functional form of the link function. We refer here to Burda (1995) Horowitz (1993) In generalizing generalized linear models, we would like to post a certain caveat. A simple ....

Maddala, G. S. (1983). Limited-dependent and qualitative variables in econometrics, Econometric Society Monographs No. 4, Cambridge University Press.

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Maddala, G. S., 1984, Limited-dependent and qualitative variables in econometrics. Cambridge: Cambridge University Press.

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Maddala, G.S. (1983) Limited-dependent and qualitative variables in econometrics, Cambridge: Cambridge University Press.

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Maddala, G.S. (1983), Limited Dependent and Qualitative Variables in Econometrics, Cambridge University Press, Cambridge.

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Maddala G.S. (1983) "Limited-Dependent and qualitative variables in econometrics. " Cambridge University Press.

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Maddala, G.S., 1987. Limited dependent and qualitative variables in econometrics. Cambridge University Press, New York.

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Maddala, G.S. (1992), Limited Dependent and Qualitative Variables in Econometrics, Cambridge University Press, Cambridge/New York/Oakleigh, 401 pp.

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Maddala, G.S., Limited Dependent and Qualitative Variables in Econometrics, Econometrics Society Monographs, Cambridge University Press, 1983, 401 p.

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Maddala, G.S. (1983) Limited-dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press.

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Maddala, G.S. (1983). Limited-dependent and Qualitative Variables in Econometrics.

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Maddala, G. S. Limited-Dependent and Qualitative Variables in Econometrics. Cambridge: Cambridge University Press, 1983.

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Maddala, G. (1989) Limited Dependent and Qualitative Variables in Econometrics, Cambridge: Cambridge University Press.

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Maddala, G. S., 1983. Limited Dependent and Qualitative Variables in Econometrics (Cambridge University Press).

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MADDALA, G. (1983): "Limited-dependent and qualitative variables in econometrics", Ed. Cambridge University Press, Cambridge.

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Maddala, G.S., 1983, Limited dependent and qualitative variables in Econometrics, Cambridge University Press, Cambridge

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MADDALA, G. S. (1983), Limited Dependent and Qualitative Variables in Econometrics, Econometric Society Monograph No. 3, Cambridge: Cambridge University Press.

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Maddala, G. S., Limited-Dependent and Qualitative Variables in Econometrics. 1983, New York: McGraw-Hill.

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Maddala, G.S., 1983, Limited Dependent and Qualitative Variables in Econometrics ( Cambridge University Press, Cambridge, U.K.).

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Maddala, G. S., 1983, Limited Dependent and Qualitative Variables in Econometrics.

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Maddala, G. (1983). Limited-Dependent and Qualitative Variables in Econometrics, New York: Cambridge University Press.

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Maddala, G. S., Limited-Dependent and Qualitative Variables in Econometrics. 1983, New York: McGraw-Hill.

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MADDALA, G.S. (1983): Limited-dependent and qualitative variables in econometrics, Cambridge: Cambridge University Press, 1983.

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