Type | Report |
Title | Developing consistent marginal effect estimates in a simulataneous equation model with limited dependent variables |
Author(s) | |
Publication (Day/Month/Year) | 2013 |
URL | https://www.researchgate.net/profile/Joseph_Atwood/publication/267254817_DEVELOPING_CONSISTENT_MARGINAL_EFFECT_ESTIMATES_IN_A_SIMULATANEOUS_EQUATION_MODEL_WITH_LIMITED_DEPENDENT_VARIABLES/links/5583314f08aefa35fe30b7b6.pdf |
Abstract | Economic studies often utilize data that is the result of simultaneously determined choices and/or simultaneously occurring economic forces. Examples of simultaneous determination include market prices and quantities, work/leisure decisions, and technology adoption. A common and complicating feature of many studies is that one or more of the observed endogenous variables may be observed only as a limited dependent variable. Later in the paper we discuss the results of a study with simultaneously determined limited dependent variables occurring as discrete indicators of whether given technologies was adopted or not. In development research the researcher is commonly interested in examining or identifying the marginal effect of one or more personal or demographic characteristics and/or governmental policies upon the likelihood of adopting a particular set of technologies. In our study we are interested in the factors influencing the likelihood of a developing country?s producers choosing to utilize improved seed varieties and chemical fertilizer. In this situation it is probable that the decisions of whether to use improved seed and/or chemical fertilizer are made concurrently and both are likely to be dependent upon unobserved latent variables. For our study, we use the classical assumption of an unobserved random utility function in which the decision to adopt is yes if the expected utility exceeds some threshold level ? . While we utilize a pair of classical probit models below, the complications discussed in this paper are relevant over a broader range of models including multistage decision models and systems with combinations of continuous, truncated, and/or binary endogenous variables. Indeed this paper?s example is a small part of a larger study in which we examine a number of indicators of technology use including combinations of continuous, truncated, and binary endogenous variables. Given the combinations of continuous, truncated, and binary endogenous dependent variables in our broader study, an obvious choice was to consider the two stage process presented by Nelson and Olson (1978). |
» | Ethiopia - Agricultural Sample Survey, Belg Season 2007-2008 (2000 E.C) |