Samuel Wills

Optimal Monetary Responses to Oil Discoveries

This paper studies how monetary policy should respond to news about an oil discovery, using a workhorse New Keynesian model. Good news about future production can create a recession today under exchange rate pegs and a simple Taylor rule, as seen in practice. This is explained by forward-looking inflation. Recession is avoided by a Taylor rule that accommodates changes in the natural level of output, which closely approximates optimal policy. Central banks have an incentive to exploit oil revenues by appreciating the terms of trade, creating “Dutch disease” and a deflationary bias which is overcome by committing to future policy.

Left in the Dark? Oil and Rural Poverty

Do oil booms reduce rural poverty and inequality? To study this we measure rural poverty by counting people who live in darkness at night: combining high-resolution global satellite data on night-time lights and population from 2000 to 2013. We develop a measure that accurately identifies 74% of households as above or below the extreme poverty line when compared to over 600,000 household surveys. We find that both high oil prices and new discoveries increase illumination and GDP nationally. However, they also promote regional inequality because the increases are limited to towns and cities with no evidence that they benefit the rural poor.

A Sectoral Framework for Analyzing Money, Credit and Unconventional Monetary Policy

This paper sets out an empirical framework for examining the dynamics of money and credit at a sectoral level. Our purpose is to understand and monitor the transmission mechanisms of different policies that affect the financial sector, with an eye to practical policy analysis. We use the banking system’s balance sheet as an organising framework and model the stocks of broad money and credit held by different sectors. Each sector is modelled as a separate block with money, credit, and sectoral expenditure modelled jointly together with the relevant financial yields. The sectors are then knitted together using aggregate relationships and identities. Overall the model can be thought of as an estimated disaggregated version of the IS-LM-CC model which additionally incorporates the principle that ‘loans create deposits’. We illustrate, by example, how this framework can be used in practice: first by examining the sectoral transmission of quantitative easing and second, the effect of disturbances to credit markets. We also discuss how other policy tools, such as the Funding for Lending Scheme and macroprudential policies, could be examined in our framework.