In agricultural economics, production functions are often estimated by relating farm profits per acre (Y) to inputs for the production of agricultural commodities. A simple model of these inputs is one with controls for weather during the growing season (W) and an indicator of land quality (L), which is assumed to be constant over time. Suppose that both S and fB2are known to be positive parameters. The production function would then be specified as follows: Yit = Bo + B1Wit + B2l + Uit where /i is an index for farms, and t indexes time. Yi: denotes farm profits per acre at farm i in year t, Wi denotes the growing season weather for farm i and year t, and L; denotes the land quality for farm i. (a) Assume that land quality is unobservable but is positively correlated with Wj.. Explain why the OLS estimator of 1 over-estimates the \"true\" f; in the case of a single cross- section, i.e., if you attempt to estimate the above regression with a single year of data. (b) Suppose you have data for two years (so t=1,2). Present a transformation of the data that would allow you to obtain a consistent estimator for 1 and write the corresponding regression equation