not apply and those that had their loan application rejected. We study formal and informal loans market separately because of the small fraction of participants in both markets.

# **6.1 Empirical methodology**

Following the methodology of Bigsten and others ( 2003), we estimate the “demand equation” and the “access equation” (or alternatively the “supply” equation) jointly. The “access equation” only includes those individual entrepreneurs or enterprises with a demand for loans. This implies that the “demand equation” acts as a “selection equation,” controlling for the endogenous self-selection process in determining loan demand, and is estimated in the first stage. In the second stage, the probability of access is estimated only for those with demand. The equations estimated are: where **_X_** denotes a vector of variables related to the demand and supply of loans, including household, personal, and business characteristics as well as location-specific indicators of economic conditions.<sup>15</sup> We include a number of variables to capture collateral availability, cash flow indicators, alternative sources of credit (supplier credit), and other variables to control for business heterogeneity. The success of the selection model depends on having variables that affect the demand for loans but do not affect the lender’s decision on access. This set of variables, which are not directly observable by the lender, corresponds to **_Z_** , referred to as “demand identification” variables.

For individual entrepreneurs, the first group of variables includes sociodemographic variables that may influence the demand and supply of loans. Educational attainment may capture managerial skills, household wealth, and capacity to negotiate with lenders. A low level of education can act as a financial market entry barrier given the complexity of financial transactions (Schrieder, 1996). Ethnicity and gender (microentrepreneurs only) may be an important determinant of a household’s social network and access to information. Moreover, indigenous people and women may be the subject of discrimination by some lenders. The number of people in the household may affect the demand for loans because it proxies for the life-cycle stage of the household and thus for its desire to invest or its probability of having an emergency. We include the availability of other sources of household income, such as remittances and PROCAMPO (farmers only).

The second set of variables encompasses characteristics of entrepreneurial activities. It includes indicators of firm size and collateral availability, such as age of activity, value of productive assets, formal or informal savings, and number of workers. Furthermore, it includes indicators of formality (registration with government institutions), social capital (membership with guilds), and training. In the regression for farmers we include indicators of land quality (irrigation) and land tenure (ejido), whether products are

> the application. In the absence of such variables we cannot be sure that we identify the application decision as opposed to the lender’s decision to grant the loan.

> 15 Economic theory emphasizes that both household and business characteristics are important in determining the demand and supply of credit. The survey data allows for a unique opportunity to control for both groups of variables.

11