First, we show that simple geographic forces play a role in understanding differences in current prosperity and income. This can be partially traced back to deep roots, such as the Agricultural Revolution, which allowed for a transition from a hunter-gatherer society to a farmer society and enabled the building of institutions (this gave the Eurasian continent a head start). Second, we analyse the importance of geo-human interaction for explaining current prosperity levels. There is special attention for the role of embodied institional knowledge incorporated in international migration flows for helping us understand the ancestry-adjusted impact of bio-geographic and institutional factors (which helps explain the reversal of fortune hypothesis). Eventually, bio-geographic factors are thus important for economic development levels, either directly or indirectly through geo-human interaction.

In this chapter, we analyse the rationale of regional policies, discuss the evidence, and highlight some methodological problems. In doing so, we also take a closer look at policy consequences that follow from or can be linked to the models discussed throughout the book. In some of our thought-experiments, we take the models of the book literally and ask, what would be the lessons for policy makers? When we discuss actual cluster/regional policy thinking, but also when we discuss hypothetical policies by sticking as closely as possible to our models, there are always three main elements to take into account. First, whether it is a people- or place-based policy (or a mix of these two). Second, to go beyond the observation that a policy can change spatial economic outcomes by showing that a policy is somehow welfare improving. Third, to take into consideration the important macro/micro distinction in terms of regional policy effectiveness: a ‘good’ regional policy at the city or regional level does not necessarily imply that it is also beneficial for the economy as whole. The main message of the chapter is that regional policies should be handled with care.

Economic activity is unevenly distributed across space, or spiky. Measuring this spikiness is not trivial. A good measure is comparable across space, comparable across sectors, unbiased regarding spatial and sector classification, and should provide a measure of significance. No measure fulfils all these criteria, but some are better than others. Once spikiness is identified the next question is ‘so what?’ Does spatial agglomeration stimulate productivity? Econometric methods to deal with this question and tackle the problem of reverse causality are: difference-in-differences, natural experiments, and regression discontinuity design. These techniques are introduced in this chapter.

Oil is a liquid mixture of hydrocarbons, usually found in rock. It is also called petroleum (Figure 5.1) The Latin roots of the word “petroleum” mean rock oil. In earlier times it was called rock oil to distinguish it from vegetable oils like rapeseed oil and animal oils like whale oil. Many different molecules may be present in petroleum. Examples are heptane and isooctane, which are used to define the octane scale for gasoline (Figure 5.2). Normal heptane is zero on the octane scale and isooctane is 100. Mixtures with higher octane numbers are more resistant to premature detonation in a spark-ignition engine. The isooctane carbon chain has branches that give it a higher octane number. Oil seeps have been known for thousands of years, and on a small scale, oil was skimmed off the surface of ponds and recovered from wells dug by hand. It was mainly used in medicines, particularly for skin ailments.

Coal is a black rock that burns (Figure 4.1). The surface of coal can be shiny, and in the 1800s it was popular to polish it to make a gemstone called jet. Queen Victoria had a jet mourning necklace. Figure 4.2 shows a representative portion of the chemical structure of coal. It is formed of irregular sheets of linked carbon rings. When coal burns the carbon atoms are oxidized to form carbon dioxide and the hydrogen atoms produce water vapor. There is also sulfur, which produces sulfur dioxide, a major pollutant. Coal reigned as the most important energy source from 1888 through 1956 (Figure 1.4). During this time coal provided double the energy of wood and water (Figure 1.6). Coal-powered locomotives and ships enabled fast long-distance transportation over land and sea for the first time. Coal stoves allowed people to heat their homes comfortably.

Let us begin by describing the sort of energy we are interested in. In this book, our emphasis will be on useful energy, energy that people apply to their purposes, like heat from a wood stove (Figure 1.1) or the energy derived from eating rice (Figure 1.2). Nowadays most of us buy our energy, although some people do split their own firewood. The energy supply is the amount that producers sell, like the 562 million tonnes of oil that flowed from Saudi wells in 2017. The energy demand is the amount that consumers buy, like gasoline for a car and electricity to light a home. Energy sales are an important part of the economy, and for this reason most countries keep good energy statistics, although they often miss the energy that people generate for themselves, like the firewood they split and the electricity from home solar panels (Figure 1.3). For energy statistics, a useful publication is the BP Statistical Review of World Energy, which has been published annually by the oil company since 1951.

The possible sources and mechanisms underlying urban agglomeration economies cannot be tested directly, which implies that empirical research uses approximations for agglomeration economies, like city size, density, economic specialization, or human capital. Since these are all endogenous variables, any effect on city wages or productivity cannot be taken as direct evidence of the relevance of agglomeration economies. This chapter discusses modern studies that use micro-data in combination with instrumental variables or fixed effects to assess the relevance of agglomeration economies. Apart from the use of micro-data and clever empirical estimation strategies, we also discuss several alternative strategies for urban economics to further increase our knowledge of the location choices made by people as well as firms between cities. Among these alternative strategies are the quasi-experimental research design, the integration of the two main building blocks (spatial equilibrium and agglomeration economies) in urban economics, a shift of attention from agglomeration benefits to costs, and looking outside the field of economics.