15 _Ni_<sup>_F_landowningfarmers,with</sup><sup>_N e_</sup> _i_<sup>+</sup><sup>_N m_</sup> _i_<sup>+</sup><sup>_N F_</sup> _i_ = _Ni_ . Additionally, there is a set of Sri Lankan middlemen who are in charge of domestic fertilizer markets (i.e. they own the domestic fertilizer endowment and also import foreign fertilizer to sell in Sri Lanka).<sup>38</sup> There are two main economic sectors, agriculture ( **A** ) and manufacturing ( **M** ). Agriculture encompasses a finite set of _K_ crops. Each crop (as well as the manufacturing good) is differentiated by regional origin (i.e., the Armington assumption). Furthermore, there is an additional minor sector, fertilizer ( **f** ), which is a single homogeneous good that is exclusively used as an intermediate input in agriculture. All markets are perfectly competitive.

# **V.B Production**

This section presents our assumptions concerning production and trade costs in each of the three sectors of the economy: agriculture, manufacturing, and fertilizer.

## **V.B.1 Agricultural Production**

We model agricultural production similarly to Farrokhi and Pellegrina (2023). Each region _i_ has an agricultural land mass of area _Lik_ that can only be used to grow crop _k_ .<sup>39</sup> This land mass is composed of a continuum of plots indexed by _ω_ , each of size _lik_ ( _ω_ ), which can be used in combination with labor and fertilizer inputs to produce agricultural goods. By combining a land portion of size _lik_ ( _ω_ ) within plot _ω_ with labor input _nik_ ( _ω_ ) and fertilizer input _fik_ ( _ω_ ), it is possible to produce an amount _qik_ ( _ω_ ) of crop _k_ according to the following Cobb-Douglas production function: where _Tik_<sup>_A_is a land productivity parameter and (</sup><sup>_γ_</sup> _k_<sup>_n_,</sup><sup>_γ_</sup> _k_<sup>_f_,</sup><sup>_γ_</sup> _k_<sup>_l_) are Cobb-Douglas coefficients.40These</sup> assumptions allow fertilizer dependence to vary across crops (since parameter _γk_<sup>_f_dependson</sup><sup>_k_),</sup> which was shown earlier to be the case. Furthermore, since productivity parameter _Tik_<sup>_A_varies across</sup> regions, they may differ in terms of absolute and comparative advantage within agriculture.

Individual production decisions can be aggregated to obtain crop production and land rents at the regional level. For a plot _ω_ producing crop _k_ in region _i_ , the optimal unit production cost _cik_ ( _ω_ ) that results from solving its cost minimization problem can be written as:

> 38For modelling convenience, we assume the population of middlemen has measure zero, so they can be omitted from the calculation of average welfare changes in Section VII. See Appendix F for further discussion of this assumption.

> 39This assumption implies that land cannot be reallocated across crops, which is consistent with the short-term horizon of our empirical implementation of the model. Importantly, this assumption finds strong support in the Ozdogan et al. (2024) remote sensing estimates of cultivated rice areas in Sri Lanka, which indicate an extremely high correlation in the pixels classified as growing rice in each year relative to the previous year (for either Maha or Yala seasons). We also provide evidence of no post-ban reduction in cultivated rice area in Appendix C.D.

> 40 _n_ We assume agricultural production functions have constant returns to scale, so _γk_<sup>+</sup><sup>_γ_</sup> _k_<sup>_f_+</sup><sup>_γ_</sup> _k_<sup>_l_= 1 for each crop</sup><sup>_k_.</sup>