{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "historic-dialogue", "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "import warnings\n", "\n", "warnings.filterwarnings(\"ignore\")" ] }, { "cell_type": "markdown", "id": "defined-scotland", "metadata": {}, "source": [ "# Spatial Inequality Dynamics\n", "\n" ] }, { "cell_type": "markdown", "id": "legendary-graduation", "metadata": { "ein.tags": "worksheet-0", "slideshow": { "slide_type": "-" } }, "source": [ "\n", "This chapter uses economic inequality to illustrate how the study of the evolution of social \n", "disparities can benefit from an explicitly spatial treatment.\n", "Social and economic inequality is often at the top of policy makers' agendas.\n", "Its study has always drawn considerable attention in academic circles.\n", "Much of the focus has been on *interpersonal income inequality*, on differences between individuals irrespective of the geographical area where they leave. Yet there is a growing recognition\n", "that the question of *inter-regional income inequality* requires further \n", "attention as the growing gaps between poor and rich regions have been identified\n", "as key drivers of civil unrest {cite}`ezcurra2019` and political polarization in developing and developed countries\n", "{cite}`Rodriguez_Pose_2018`.\n", "\n", "## Introduction\n", "\n", "Much of the study of inequalities has focused at the individual level: how do outcomes\n", "differ across individuals? This approach does not group individuals geographically. \n", "In other words, it is not concerned with whether those differences follow a pattern,\n", "for example, at the regional level (e.g., *is most of the more disadvantaged population\n", "located in a particular section of the map?*).\n", "Indeed, while the two literatures (personal and regional inequality) are\n", "related, they have developed in a largely parallel fashion with limited\n", "cross-fertilization. In this chapter, we examine how a spatially explicit focus\n", "can provide insights on the study of inequality and its dynamics. We hope this illustration\n", "can be useful in itself but also inspire the use of these methods in the study of\n", "other phenomena for which the regional perspective can bring value. This is also the only chapter where\n", "we explicitly deal with time as an additional dimension. Our presentation of inequalities takes\n", "an inherently temporal view, considering how different indices evolve over time the the extent to which a spatial pattern changes. Again, we hope the illustration we show here with inequality indices has value\n", "in itself, but also as inspiration for how to tackle time and dynamics in broader contexts.\n", "\n", "After discussing the data we employ, we begin with an introduction to classic methods for interpersonal income\n", "inequality analysis and how they have been adopted to the question of regional\n", "inequalities. These include a number of graphical tools alongside familiar\n", "indices of inequality. As we discuss more fully, the use of these classical\n", "methods in spatially referenced data, while useful in providing insights on some\n", "of the aspects of spatial inequality, fails to fully capture the nature of\n", "geographical disparities and their dynamics. Thus, we next move to spatially\n", "explicit measures for regional inequality analysis. The chapter closes with\n", "some recent extensions of some classical measures to more fully examine the\n", "spatial dimensions of regional inequality dynamics.\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "light-sierra", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [], "source": [ "import seaborn\n", "import pandas\n", "import geopandas\n", "import pysal\n", "import numpy\n", "import mapclassify\n", "import matplotlib.pyplot as plt\n", "from pysal.explore import esda\n", "from pysal.lib import weights" ] }, { "cell_type": "markdown", "id": "gross-organic", "metadata": {}, "source": [ "## Data: US State Per Capita Income 1969-2017\n", "\n", "For this chapter, we use data on average income per capita over time. Specifically, we consider the United States counties from 1969 to 2017. US Counties are small regions that fit hierarchically within states. This perspective will allow us to examine trends for individual observations (counties), or regions containing several of them in a geographically consistent way (states or Census regions which are collections of states). The temporal approach will reveal whether these entities get richer or poorer, as well as how the overall distribution of income moves, skews, or spreads out. \n" ] }, { "cell_type": "code", "execution_count": 3, "id": "exterior-african", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "text/plain": [ "Index(['STATEFP', 'COUNTYFP', 'COUNTYNS', 'GEOID', 'NAME', 'NAMELSAD', 'LSAD',\n", " 'CLASSFP', 'MTFCC', 'CSAFP', 'CBSAFP', 'METDIVFP', 'FUNCSTAT', 'ALAND',\n", " 'AWATER', 'INTPTLAT', 'INTPTLON', 'GeoFIPS', 'GeoName', 'Region',\n", " 'TableName', 'LineCode', 'Descriptio', 'Unit', '1969', '1970', '1971',\n", " '1972', '1973', '1974', '1975', '1976', '1977', '1978', '1979', '1980',\n", " '1981', '1982', '1983', '1984', '1985', '1986', '1987', '1988', '1989',\n", " '1990', '1991', '1992', '1993', '1994', '1995', '1996', '1997', '1998',\n", " '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007',\n", " '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015', '2016',\n", " '2017', 'index', 'IndustryCl', 'Descript_1', 'geometry'],\n", " dtype='object')" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pci_df = geopandas.read_file(\n", " \"../data/us_county_income/uscountypcincome.gpkg\"\n", ")\n", "pci_df.columns" ] }, { "cell_type": "markdown", "id": "devoted-bristol", "metadata": { "ein.tags": "worksheet-0", "slideshow": { "slide_type": "-" } }, "source": [ "Inspection of the column names reveals that the table is organized around one row per county, and with the years as columns, together with information about the particular record.\n", "This format is an example of a *wide* longitudinal data set.\n", "In wide-format data, each column represents a different time period, meaning that each row represents a set of measurements made about the same \"entity\" over time (as well as any unique identifying information about that entity.)\n", "This contrasts with a *narrow*, *long* format, where each row describes an entity at a specific point in time. \n", "Long data results in significant duplication for records and is generally worse for data storage, particularly in the geographic case. However, long form data is sometimes a more useful format when manipulating and analyzing data, as {cite}`wickham2014tidy` discusses. Nonetheless, when analyzing *trajectories*, that is, the paths that entities take over time, wide data is more useful, and we will use that here. \n", "\n", "In this dataset, we have 3076 counties across 49 years, as well as 28 extra columns that describe each county. \n", "\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "characteristic-money", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "text/plain": [ "(3076, 77)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pci_df.shape" ] }, { "cell_type": "markdown", "id": "knowing-nowhere", "metadata": {}, "source": [ "As an example, we can see the first ten years for Jackson County, Mississippi (state code `28`) below:" ] }, { "cell_type": "code", "execution_count": 5, "id": "opposed-virgin", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
19691970197119721973197419751976197719781979
141729573121332739394203454754615927631566196967
\n", "
" ], "text/plain": [ " 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979\n", "1417 2957 3121 3327 3939 4203 4547 5461 5927 6315 6619 6967" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pci_df.query('NAME == \"Jackson\" & STATEFP == \"28\"').loc[\n", " :, \"1969\":\"1979\"\n", "]" ] }, { "cell_type": "markdown", "id": "illegal-dietary", "metadata": { "ein.tags": "worksheet-0", "slideshow": { "slide_type": "-" } }, "source": [ "## Global Inequality\n", "\n", "We begin our examination of inequality by focusing on several global measures of income inequality. Here, \"global\" means that the measure is concerned with the overall nature of inequality within the income distribution. That is, these measures focus on the direct disparity between rich and poor, considering nothing about where the rich and poor live. Several classic measures of inequality are available for this purpose. \n", "\n", "In general terms, measures of inequality focus on the dispersion present in an income distribution. In the case of regional or spatial inequality, the distributions describe the average or per capita incomes for spatial units, such as for counties, census tracts, or regions. For our US county data, we can visualize the distribution of per capita incomes for the first year in the sample as follows:" ] }, { "cell_type": "code", "execution_count": 6, "id": "large-sullivan", "metadata": { "caption": "Distribution of U.S. Per Capita Income at County Level in 1969.", "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "lines_to_next_cell": 2, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "seaborn.histplot(x=pci_df[\"1969\"], kde=True);" ] }, { "cell_type": "markdown", "id": "julian-campus", "metadata": {}, "source": [ "Looking at this distribution, notice that the right side of the distribution is much longer than the left side. This long right tail is a prominent feature, and is common in the study of incomes and many other societal phenomena, as it reflects the fact that within a single income distribution, the super-rich are generally much more wealthy than the super-poor are deprived, compared to the average. \n", "\n", "A key point to keep in mind here is that the unit of measurement in this data is a spatial aggregate of individual incomes. Here, we are using the per capita incomes for each county. By contrast, in the wider inequality literature, the observational unit is typically a household or individual. In the latter distributions, the degree of skewness is often more pronounced. This difference arises from the smoothing that is intrinsic to aggregation: the regional distributions are based on averages obtained from the individual distributions, and so the extremely high-income individuals are averaged with the rest of their county. The regional approach implies that, to avoid falling into the so-called \"ecological fallacy\", whereby individual conclusions are drawn from geographical aggregates, our conclusions will hold at the area level (the *county*) rather than the individual one (the *person*)." ] }, { "cell_type": "markdown", "id": "guided-hearts", "metadata": {}, "source": [ "The kernel density estimate (or histogram) is a powerful visualization device that captures the overall morphology of the *feature* distribution for this measure of income. At the same time, the plot is silent on the underlying *geographic distribution* of county incomes. We can look at this second view of the distribution using a choropleth map. To construct this, we can use the standard `geopandas` plotting tools. \n", "\n", "Before we can get to mapping, we change the CRS to a suitable one for mapping, the Albers Equal Area projection for North America: " ] }, { "cell_type": "code", "execution_count": 7, "id": "fossil-wound", "metadata": {}, "outputs": [], "source": [ "pci_df = pci_df.to_crs(\n", " # Albers Equal Area North America\n", " epsg=5070\n", ")" ] }, { "cell_type": "markdown", "id": "immediate-actress", "metadata": {}, "source": [ "And the (quantile) choropleth for 1969 can be generated by:" ] }, { "cell_type": "code", "execution_count": 8, "id": "bottom-particle", "metadata": { "caption": "Quintiles of Per Capita Income by County, 1969", "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = pci_df.plot(\n", " column=\"1969\",\n", " scheme=\"Quantiles\",\n", " legend=True,\n", " edgecolor=\"none\",\n", " legend_kwds={\"loc\": \"lower left\"},\n", " figsize=(12, 12),\n", ")\n", "ax.set_axis_off()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "integral-gateway", "metadata": { "lines_to_next_cell": 0 }, "source": [ "The choropleth and the kernel density provide different visual depictions of the distribution of county incomes. The kernel density estimate is a *feature*-based representation, and the map is a *geographic*-based representation. Both are useful for developing a more comprehensive understanding. To gain insights on the level of inequality in the distribution, we'll discuss a few indices common in the statistical and econometric literatures. \n", "\n", "### 20:20 Ratio\n", "\n", "One commonly used measure of inequality in a distribution is the so called 20:20 ratio, which is defined as the ratio of the incomes at the 80th percentile over that at the 20th percentile: \n", "" ] }, { "cell_type": "code", "execution_count": 9, "id": "iraqi-czech", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "lines_to_next_cell": 2, "slideshow": { "slide_type": "-" } }, "outputs": [], "source": [ "top20, bottom20 = pci_df[\"1969\"].quantile([0.8, 0.2])" ] }, { "cell_type": "markdown", "id": "amino-overhead", "metadata": {}, "source": [ "The `top20` (`bottom20`) objects contain the boundary value that separates the series between the top (bottom) 20% of the distribution and the rest. With these, we can generate the ratio:" ] }, { "cell_type": "code", "execution_count": 10, "id": "surprising-relations", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.5022494887525562" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top20 / bottom20" ] }, { "cell_type": "markdown", "id": "peripheral-makeup", "metadata": { "ein.tags": "worksheet-0", "slideshow": { "slide_type": "-" } }, "source": [ "In 1969 the richest 20% of the counties had an income that was 1.5 times the poorest 20% of the counties. The 20:20 ratio has the advantage of being robust to outliers at the top and the bottom of the distribution. To look at the dynamics of this global inequality measure, one way is to create a function that calculates it for a given year, and apply it to all years in our time series:" ] }, { "cell_type": "code", "execution_count": 11, "id": "broadband-jason", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def ineq_20_20(values):\n", " top20, bottom20 = values.quantile([0.8, 0.2])\n", " return top20 / bottom20\n", "\n", "\n", "# Generate range of strings from 1969 to 2018\n", "years = numpy.arange(1969, 2018).astype(str)\n", "# Compute 20:20 ratio for every year\n", "ratio_2020 = pci_df[years].apply(ineq_20_20, axis=0)\n", "# Plot evolution of 20:20 ratio\n", "ax = plt.plot(years, ratio_2020)\n", "\n", "# Grab figure generated in the plot\n", "figure = plt.gcf()\n", "# Replace tick labels with every other year\n", "plt.xticks(years[::2])\n", "# Set vertical label\n", "plt.ylabel(\"20:20 ratio\")\n", "# Set horizontal label\n", "plt.xlabel(\"Year\")\n", "# Rotate year labels\n", "figure.autofmt_xdate(rotation=45)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "industrial-collection", "metadata": { "ein.tags": "worksheet-0", "slideshow": { "slide_type": "-" } }, "source": [ "The evolution of the ratio has a U-shaped pattern over time, bottoming out around 1994 after a long decline. Post 1994, however, the 20:20 ratio indicates there is increasing inequality up until 2013, where there is a turn towards lower income inequality between the counties." ] }, { "cell_type": "markdown", "id": "reflected-hartford", "metadata": { "ein.tags": "worksheet-0", "lines_to_next_cell": 2, "slideshow": { "slide_type": "-" } }, "source": [ "In addition to the 20/20 ratio, we will explore two more traditional measures of inequality: the Gini and Theil's indices. For these, we will use the `inequality` package from Pysal." ] }, { "cell_type": "code", "execution_count": 12, "id": "radio-construction", "metadata": {}, "outputs": [], "source": [ "from pysal.explore import inequality" ] }, { "cell_type": "markdown", "id": "speaking-fabric", "metadata": { "ein.tags": "worksheet-0", "slideshow": { "slide_type": "-" } }, "source": [ "### Gini Index\n", "\n", "The Gini index is a longstanding measure of inequality based on the notion of cumulative wealth distribution {cite}`manz2021`. The Gini is closely linked to another popular device called the Lorenz curve\n", ". To construct a Lorenz curve, the cumulative share of wealth is plotted against the share of the population that owns that wealth. For example, in an extremely unequal society where few people own nearly all the wealth, the Lorenz curve increases very slowly at first, then skyrockets once the wealthiest people are included. \n", "\n", "In contrast, a \"perfectly equal\" society would look like a straight line connecting $(0,0)$ and $(1,1)$. This is called the *line of perfect equality*, and represents the case where $p$% of the population owns exactly $p$% of the wealth. For example, this might mean that 50% of the population earns exactly 50% of the income, or 90% of the population owns 90% of the wealth. The main idea is that the share of wealth or income is exactly proportional to the share of population that owns that wealth or earns that income, which occurs only when everyone has the same income or owns the same amount of wealth. \n", "\n", "With these notions in mind, we can define the Gini index as the ratio of the area between the line of perfect equality and the Lorenz curve for a given income or wealth distribution, standardized by the area under the line of perfect equality (which is always $\\frac{1}{2}$). Thus, the Gini index is a measure of the gap between a perfectly equal society and the observed society over every level of wealth/income. \n", "\n", "We can construct the Lorenz curve for 1969 by first computing the share of our population of counties that is below each observation. For that, we generate a cumulative series:" ] }, { "cell_type": "code", "execution_count": 13, "id": "nuclear-jenny", "metadata": {}, "outputs": [], "source": [ "n = len(pci_df)\n", "share_of_population = numpy.arange(1, n + 1) / n" ] }, { "cell_type": "markdown", "id": "solid-wagner", "metadata": {}, "source": [ "Then, we consider the cumulative evolution of income. For this, we need to find out the proportion of total income owned by each share of the population. Empirically, this can be computed in the following fashion. First, we sort county incomes:" ] }, { "cell_type": "code", "execution_count": 14, "id": "alpine-criminal", "metadata": {}, "outputs": [], "source": [ "incomes = pci_df[\"1969\"].sort_values()" ] }, { "cell_type": "markdown", "id": "graphic-hunter", "metadata": {}, "source": [ "Second, we find the overall percentage of income accumulated at each data point. To do this, we compute what percentage of the total income that of each county represents:" ] }, { "cell_type": "code", "execution_count": 15, "id": "excellent-internet", "metadata": {}, "outputs": [], "source": [ "shares = incomes / incomes.sum()" ] }, { "cell_type": "markdown", "id": "frank-latter", "metadata": {}, "source": [ "and construct the *cumulative sum* of these shares, which reflects the sum of all of the shares of income up to the current one:\n", "\n", "$$ \\texttt{CumSum(v, k)} = \\sum_{i=1}^k v_i$$\n", "\n", "This starts at $0$ and reaches $1$ once the last share is included:" ] }, { "cell_type": "code", "execution_count": 16, "id": "dirty-intermediate", "metadata": {}, "outputs": [], "source": [ "cumulative_share = shares.cumsum()" ] }, { "cell_type": "markdown", "id": "cordless-antibody", "metadata": {}, "source": [ "With this, we can plot both the Lorenz curve and the line of perfect equality:" ] }, { "cell_type": "code", "execution_count": 17, "id": "united-investor", "metadata": { "caption": "The Lorenz Curve for county Per Capita Income 1969.", "lines_to_next_cell": 0, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Generate figure with one axis\n", "f, ax = plt.subplots()\n", "# Plot Lorenz Curve\n", "ax.plot(share_of_population, cumulative_share, label=\"Lorenz Curve\")\n", "# Plot line of perfect equality\n", "ax.plot((0, 1), (0, 1), color=\"r\", label=\"Perfect Equality\")\n", "# Label horizontal axis\n", "ax.set_xlabel(\"Share of population\")\n", "# Label vertical axis\n", "ax.set_ylabel(\"Share of income\")\n", "# Add legend\n", "ax.legend()\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "ready-longer", "metadata": {}, "source": [ "The blue line is the Lorenz curve for county incomes in 1969. The Gini index is the area between it and the 45-degree line of equality shown in red, all standardized by the area underneath the line of equality.\n", "\n", "A first approach to examine how inequality has evolved is to plot the Lorenz curves for each year. One way to do this in Python involves creating a function that will compute the Lorenz curve for an arbitrary set of incomes. The following function encapsulates the steps shown above into a single shot:" ] }, { "cell_type": "code", "execution_count": 18, "id": "prime-safety", "metadata": {}, "outputs": [], "source": [ "def lorenz(y):\n", " y = numpy.asarray(y)\n", " incomes = numpy.sort(y)\n", " income_shares = (incomes / incomes.sum()).cumsum()\n", " N = y.shape[0]\n", " pop_shares = numpy.arange(1, N + 1) / N\n", " return pop_shares, income_shares" ] }, { "cell_type": "markdown", "id": "floating-protocol", "metadata": {}, "source": [ "For a single year, say 1969, our function would return a tuple with two arrays, one for each axis in the Lorenz curve plot:" ] }, { "cell_type": "code", "execution_count": 19, "id": "working-donna", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([3.25097529e-04, 6.50195059e-04, 9.75292588e-04, ...,\n", " 9.99349805e-01, 9.99674902e-01, 1.00000000e+00]),\n", " array([1.22486441e-04, 2.52956561e-04, 3.83636778e-04, ...,\n", " 9.98429316e-01, 9.99176315e-01, 1.00000000e+00]))" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lorenz(pci_df[\"1969\"])" ] }, { "cell_type": "markdown", "id": "pending-quarter", "metadata": { "lines_to_next_cell": 0 }, "source": [ "We can now use the same strategy as above to calculate the Lorenz curves for all the years in our datasets:" ] }, { "cell_type": "code", "execution_count": 20, "id": "verified-karaoke", "metadata": {}, "outputs": [], "source": [ "lorenz_curves = pci_df[years].apply(lorenz, axis=0)" ] }, { "cell_type": "markdown", "id": "residential-auction", "metadata": {}, "source": [ "Practically, this becomes a dataframe with columns for each year. Rows contain the population shares (or income shares) as lists. We can then iterate over the columns (years) of this dataframe, generating a plot of the Lorenz curve for each year:" ] }, { "cell_type": "code", "execution_count": 21, "id": "figured-teaching", "metadata": { "caption": "Lorenz curves for county per capita incomes since 1969." }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Set up figure with one axis\n", "f, ax = plt.subplots()\n", "# Plot line of perfect equality\n", "ax.plot((0, 1), (0, 1), color=\"r\")\n", "# Loop over every year in the series\n", "for year in lorenz_curves.columns:\n", " # Extract the two arrays or each dimension\n", " year_pop_shares, year_inc_shares = lorenz_curves[year].values\n", " # Plot Lorenz curve for a given year\n", " ax.plot(year_pop_shares, year_inc_shares, color=\"k\", alpha=0.05)" ] }, { "cell_type": "markdown", "id": "welsh-lafayette", "metadata": {}, "source": [ "The compression of the Lorenz curves makes it difficult to ascertain the temporal pattern in inequality. Focusing explicitly on the Gini coefficients may shed more light on the evolution of inequality over time. \n", "\n", "Remember the Gini coefficient represents the area in between the Lorenz curve and that of perfect equality. The measure can be calculated directly through the `Gini` class in `inequality`. For 1969, this implies:" ] }, { "cell_type": "code", "execution_count": 22, "id": "spare-abuse", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [], "source": [ "g69 = inequality.gini.Gini(pci_df[\"1969\"].values)" ] }, { "cell_type": "markdown", "id": "first-whole", "metadata": {}, "source": [ "To extract the coefficient, we retrieve the `g` property of `g69`:" ] }, { "cell_type": "code", "execution_count": 23, "id": "alone-monaco", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "text/plain": [ "0.13556175504269904" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g69.g" ] }, { "cell_type": "markdown", "id": "documented-search", "metadata": {}, "source": [ "Here, the Gini coefficient in 1969 was 0.13. To compute this for every year, we can use a similar pattern as we have before. First, define a function to compute the quantity of interest; then, apply the function across the table with all years:" ] }, { "cell_type": "code", "execution_count": 24, "id": "intimate-tooth", "metadata": {}, "outputs": [], "source": [ "def gini_by_col(column):\n", " return inequality.gini.Gini(column.values).g" ] }, { "cell_type": "markdown", "id": "consolidated-grace", "metadata": {}, "source": [ "`inequality`'s Gini requires an `numpy.ndarray` rather than a `pandas.Series` object, which we can pull out through the `values` attribute. This is passed to the `Gini` class, and we only return the value of the coefficient as a `DataFrame` object." ] }, { "cell_type": "code", "execution_count": 25, "id": "applicable-picture", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [], "source": [ "inequalities = (\n", " pci_df[years].apply(gini_by_col, axis=0).to_frame(\"gini\")\n", ")" ] }, { "cell_type": "markdown", "id": "stretch-stake", "metadata": {}, "source": [ "This results in a series of Gini values, one for each year:" ] }, { "cell_type": "code", "execution_count": 26, "id": "technical-midnight", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " gini\n", "1969 0.135562\n", "1970 0.130076\n", "1971 0.128540\n", "1972 0.129126\n", "1973 0.142166" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inequalities.head()" ] }, { "cell_type": "markdown", "id": "average-segment", "metadata": {}, "source": [ "Which we can turn into a graphical representation through standard `pandas` plotting. The resulting pattern is similar to that of the 20:20 ratio above:" ] }, { "cell_type": "code", "execution_count": 27, "id": "rapid-bracelet", "metadata": { "caption": "Gini coefficients for per capita income since 1969" }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "inequalities.plot(figsize=(10, 3));" ] }, { "cell_type": "markdown", "id": "visible-presence", "metadata": {}, "source": [ "### Theil's index\n", "\n", "A third commonly used measure of inequality is Theil's $T$ {cite}`manz2021` given as:\n", "\n", "$$T = \\sum_{i=1}^m \\left( \\frac{y_i}{\\sum_{i=1}^m y_i} \\ln \\left[ m \\frac{y_i}{\\sum_{i=1}^m y_i}\\right] \\right)$$\n", "\n", "where $y_i$ is per capita income in area $i$ among $m$ areas. Conceptually, this metric is related to the entropy of the income distribution, measuring how evenly-distributed incomes are across the population.\n", "\n", "The Theil index is also available in Pysal's `inequality`, so we can take a similar approach as above to calculate it for every year:" ] }, { "cell_type": "code", "execution_count": 28, "id": "lonely-dividend", "metadata": {}, "outputs": [], "source": [ "def theil(column):\n", " return inequality.theil.Theil(column.values).T\n", "\n", "\n", "inequalities[\"theil\"] = pci_df[years].apply(theil, axis=0)" ] }, { "cell_type": "markdown", "id": "compliant-producer", "metadata": {}, "source": [ "And generate a visual comparison of its evolution over time:" ] }, { "cell_type": "code", "execution_count": 29, "id": "ancient-implementation", "metadata": { "caption": "Gini and Theil indices for county per capita income distributions since 1969.", "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "inequalities[\"theil\"].plot(color=\"orange\", figsize=(10, 3));" ] }, { "cell_type": "markdown", "id": "unlimited-blues", "metadata": {}, "source": [ "The time paths of the Gini and the Theil coefficients appear to show striking\n", "similarities. At first glance, this might suggest that the indices are\n", "substitutes for one another. However, if we plot them against each other, we can see they are not perfectly correlated: " ] }, { "cell_type": "code", "execution_count": 30, "id": "daily-entry", "metadata": { "caption": "Relationhsip between Gini and Theil indices for county per capita income distributions since 1969.", "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "_ = seaborn.regplot(x=\"theil\", y=\"gini\", data=inequalities)" ] }, { "cell_type": "markdown", "id": "further-daughter", "metadata": {}, "source": [ "Indeed, as we shall see below, each index has\n", "properties that lend themselves to particular spatial extensions that work in complementary ways. We need both (and more) for a complete picture. \n", "\n" ] }, { "cell_type": "markdown", "id": "radio-routine", "metadata": {}, "source": [ "## Personal versus Regional Income\n", "There is a subtle but important distinction between the study of personal and\n", "regional income inequality. To see this, we first need to express the\n", "relationships between the two types of inequality. Consider a country composed\n", "of $N$ individuals who are distributed over $m$ regions. Let $Y_l$ denote the\n", "income of individual $l$. Total personal income in region $i$ is given as $Y_i =\n", "\\sum_{l \\in i} Y_l$, and per capita income in region $i$ is $y_i = \\frac{Y_i}{N_i}$,\n", "where $N_i$ is the number of individuals in region $i$.\n", "\n", "At the national level, the coefficient of variation in incomes could be used as an index of interpersonal income inequality. This would be:\n", "\n", "$$CV_{nat} = \\sqrt{\\frac{\\sum_{l=1}^N (Y_l - \\bar{y})^2}{N}}$$\n", "\n", "where $\\bar{y}$ is the national average for per capita income. The key component here is the sum\n", "of squares term, and unpacking this sheds light on personal versus regional\n", "inequality question:\n", "\n", "$$TSS = \\sum_{l=1}^N (Y_l - \\bar{y})^2$$\n", "\n", "An individual deviation, $\\delta_l = Y_l - \\bar{y}$, is the contribution to inequality associated with individual $l$. We can break this into two components:\n", "\n", "$$\\delta_l = (Y_l - y_i) + (y_i - \\bar{y})$$\n", "\n", "The first term is the difference between the individual's income and per capita income in the individual's region of residence, while the second term is the difference between the region's per capita income and average national per capita income.\n", "\n", "In regional studies, the intra-regional personal income distribution is typically\n", "not available. As a result, the assumption is often made that intra-regional\n", "personal inequality is zero. In other words, all individuals in the same region\n", "have identical incomes. With this assumption in hand, the first term vanishes:\n", "$Y_l -y_i = 0$, leading to:[^reg] \n", "\n", "[^reg]: It should also be noted that even at the national scale, the analysis of interpersonal income inequality also relies on aggregate data grouping individuals into income cohorts. See, for example, {cite}`Piketty_2003`.\n", "\n", "$$\n", "\\begin{aligned}\n", "TSS &= \\sum_{l=1}^N (Y_l - \\bar{y})^2 \\\\\n", " &= \\sum_{l=1}^N \\delta_l^2 \\\\\n", " &= \\sum_{l=1}^N ((Y_l - y_i) + (y_i - \\bar{y}))^2 \\\\\n", " &= \\sum_{l=1}^N (0 + (y_i - \\bar{y}))^2 \\\\\n", " &= \\sum_{i=1}^m\\sum_{l \\in i} (y_i - \\bar{y})^2 \\\\\n", " &= \\sum_{i=1}^m [N_i(y_i - \\bar{y})]^2\n", "\\end{aligned}\n", "$$\n", "\n", "This means that each individual in a region has an equal contribution to the\n", "overall level of national interpersonal inequality, given by $(y_i - \\bar{y})$,\n", "while the region in question contributes $N_i(y_i - \\bar{y})$. While it may seem\n", "that the assumption of zero intra-regional interpersonal income inequality is\n", "overly restrictive, it serves to isolate the nature of inter-regional income\n", "inequality. That is, inequality between places, rather than inequality between\n", "people within those places. In essence, this strategy shifts the question up one\n", "level in the spatial hierarchy by aggregating micro-level individual data to\n", "areal units.\n", "\n" ] }, { "cell_type": "markdown", "id": "intellectual-traveler", "metadata": { "ein.tags": "worksheet-0", "lines_to_next_cell": 0, "slideshow": { "slide_type": "-" } }, "source": [ "## Spatial Inequality" ] }, { "cell_type": "markdown", "id": "informed-beatles", "metadata": {}, "source": [ "The analysis of regional income inequality differs from the analysis of\n", "national interpersonal income inequality in its focus on spatial units. Since\n", "regional incomes are explicitly embedded in geographical space, we can take advantage\n", "of their spatial configuration to learn more about the nature of the inequality.\n", "In the regional inequality literature this has been approached in a number of ways.\n", "Three are considered in this chapter: one that links the discussion to that of spatial\n", "autocorrelation in chapters [6](06_spatial_autocorrelation) and [7](07_local_autocorrelation);\n", "a second one based on decomposing global indices regionally; and a third one that embeds space\n", "in traditional global measures." ] }, { "cell_type": "markdown", "id": "falling-favor", "metadata": { "ein.tags": "worksheet-0", "lines_to_next_cell": 2, "slideshow": { "slide_type": "-" } }, "source": [ "### Spatial Autocorrelation\n", "\n" ] }, { "cell_type": "markdown", "id": "stupid-croatia", "metadata": {}, "source": [ "This approach helps us shed light on the properties of the spatial pattern of regional income data. We return to global measures of spatial autocorrelation that we encountered earlier in the book. The essence of this approach is to examine to what extent the spatial distribution of incomes is concentrated over space. For this, we use a queen spatial weights matrix and calculate Moran's I for\n", "each year in the sample:" ] }, { "cell_type": "code", "execution_count": 31, "id": "least-supplier", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [], "source": [ "wq = weights.Queen.from_dataframe(pci_df)" ] }, { "cell_type": "markdown", "id": "handed-manhattan", "metadata": {}, "source": [ "Following the same pattern to \"broadcast\" a function, we create a function that returns the results we need from each statistic. Here, we will also keep the pseudo $p$-value for the Moran statistic which, as we saw in [Chapter 6](06_spatial_autocorrelation), helps us identify whether the index is statistically significant under the null hypothesis that incomes are randomly distributed geographically." ] }, { "cell_type": "code", "execution_count": 32, "id": "electoral-coast", "metadata": {}, "outputs": [], "source": [ "def moran_by_col(y, w=wq):\n", " mo = esda.Moran(y, w=w)\n", " mo_s = pandas.Series(\n", " {\"I\": mo.I, \"I-P value\": mo.p_sim},\n", " )\n", " return mo_s" ] }, { "cell_type": "markdown", "id": "underlying-element", "metadata": {}, "source": [ "This time, our function returns a `Series` object so that when we pass it through `apply`, we get a well formatted table:" ] }, { "cell_type": "code", "execution_count": 33, "id": "remarkable-ranch", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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II-P value
19690.6490900.001
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" ], "text/plain": [ " I I-P value\n", "1969 0.649090 0.001\n", "1970 0.647438 0.001\n", "1971 0.626546 0.001\n", "1972 0.606760 0.001\n", "1973 0.640226 0.001" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "moran_stats = pci_df[years].apply(moran_by_col, axis=0).T\n", "\n", "moran_stats.head()" ] }, { "cell_type": "markdown", "id": "liberal-symposium", "metadata": {}, "source": [ "For further comparison, the results are attached to the `inequalities` table:" ] }, { "cell_type": "code", "execution_count": 34, "id": "accepting-legend", "metadata": {}, "outputs": [], "source": [ "inequalities = inequalities.join(moran_stats)" ] }, { "cell_type": "markdown", "id": "based-young", "metadata": {}, "source": [ "Which can be visualised by:" ] }, { "cell_type": "code", "execution_count": 35, "id": "biblical-multiple", "metadata": { "caption": "Relationship between the Gini & Theil inequality indices and Moran's I, a measure of spatial autocorrelation, for per capita incomes.", "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "lines_to_next_cell": 0, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "inequalities[[\"I\", \"I-P value\"]].plot(subplots=True, figsize=(10, 6))\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "growing-prospect", "metadata": { "lines_to_next_cell": 0 }, "source": [ "Several patterns emerge from the time series of Moran's I. Before delving into the details, it is worth noting that, while Gini and Theil indices from previous figures follow a similar path, Moran's I displays a distinct trajectory. There is a long-term decline in the value of Moran's I. This suggests a gradual decline in the geographic structure of inequality with two implications: (a) per capita incomes are now less similar between nearby counties and (b), this has been consistently declining, regardless of whether inequality is high or low. \n", "Second, despite this decline, there is never a year in which the spatial autocorrelation is not statistically significant. In other words, there is a strong geographic structure in the distribution of regional incomes that needs to be accounted for when focusing on inequality questions.\n", "\n", "### Regional Decomposition of Inequality\n", "\n", "One common objection to the analysis of inequality in aggregate relates to lack of detail about the scale at which inequality is most important. Inequality can be driven by differences between groups and not by discrepancies in income between similar individuals. That is, there is always the possibility that observed inequality can be \"explained\" by a confounding variate, such as age, sex, or education. For example, income differences between older and younger people can \"explain\" a large part of the societal inequality in wealth: older people have much longer to acquire experience, and thus are generally paid more for that experience. Younger people do not have as much experience, so young people (on average) have lower incomes than older people. \n", "\n", "To tackle this issue, it is often useful to *decompose* inequality indices into constituent groups. This allows us to understand how much of inequality is driven by aggregate group differences and how much is driven by observation-level inequality. This also allows us to characterize how unequal each group is separately. In geographic applications, these groups are usually spatially defined, in that *regions* are contiguous geographic groups of observations {cite}`shorrocks2005`. This section discusses regional inequality decompositions as a way to introduce geography into the study of inequality. \n", "\n", "Let's illustrate these ideas with our income dataset. The table records the United States Census Bureau region a county belongs to in the `Region` variable. These divide the country into eight regions, each assigned a number that relates to its name as specified below:" ] }, { "cell_type": "code", "execution_count": 36, "id": "impressed-illinois", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [], "source": [ "region_names = {\n", " 1: \"New England\",\n", " 2: \"Mideast\",\n", " 3: \"Great Lakes\",\n", " 4: \"Plains\",\n", " 5: \"Southeast\",\n", " 6: \"Southwest\",\n", " 7: \"Rocky Mountain\",\n", " 8: \"Far West\",\n", "}" ] }, { "cell_type": "markdown", "id": "administrative-mattress", "metadata": {}, "source": [ "We can visualize the regions with the names on the legend by first mapping the name to each region number, and then rendering a qualitative choropleth:" ] }, { "cell_type": "code", "execution_count": 37, "id": "patent-turkish", "metadata": { "caption": "Map of census regions in the United States." }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = pci_df.assign(Region_Name=pci_df.Region.map(region_names)).plot(\n", " \"Region_Name\",\n", " linewidth=0,\n", " legend=True,\n", " categorical=True,\n", " legend_kwds=dict(bbox_to_anchor=(1.2, 0.5)),\n", ")\n", "ax.set_axis_off();" ] }, { "cell_type": "markdown", "id": "skilled-maintenance", "metadata": {}, "source": [ "Let's peak into income changes for each region. To do that, we can apply a split-apply-combine pattern that groups counties by region, calculates its mean, and combines it into a table:" ] }, { "cell_type": "code", "execution_count": 38, "id": "african-convention", "metadata": {}, "outputs": [], "source": [ "rmeans = (\n", " pci_df.assign(\n", " # Create column with region name for each county\n", " Region_Name=pci_df.Region.map(region_names)\n", " )\n", " .groupby(\n", " # Group counties by region name\n", " by=\"Region_Name\"\n", " # Calculate mean by region and save only year columns\n", " )\n", " .mean()[years]\n", ")" ] }, { "cell_type": "markdown", "id": "virtual-wyoming", "metadata": {}, "source": [ "The resulting table has a row for each region and a column for each year. We can visualize these means to get a sense of their temporal trajectory:" ] }, { "cell_type": "code", "execution_count": 39, "id": "blocked-glory", "metadata": { "caption": "Average county per capita incomes among census regions since 1969" }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "rmeans.T.plot.line(figsize=(10, 5));" ] }, { "cell_type": "markdown", "id": "classified-organizer", "metadata": {}, "source": [ "One way to introduce geography into the analysis of inequality is to use geographical delineations to define groups for decompositions. For example, Theil's $T$, which we encountered previously, can be decomposed using regions into so called *between* and *within* regional inequality components.\n", "To proceed in this direction, we first re-conceptualize our observations of per capita incomes for $m$ regional economies as $y = \\left( y_1, y_2, \\ldots, y_m \\right)$. These are grouped into $\\omega$ mutually exclusive regions. Formally, this means that when $m_g$ represents the number of areas assigned to region $g$, the total number of areas must be equal to the count of all the areas in each region: $\\sum_{g=1}^{\\omega} m_g=m$.[^mut-ex] With this notation, Theil's index from above can be rewritten to emphasize its between and within components:\n", "\n", "[^mut-ex]: This would be violated, for example, if one area were in two regions. This area would get \"double counted\" in this total. \n", "\n", "$$\n", "\\begin{aligned}\n", "T &= \\sum_{i=1}^m \\left( \\frac{y_i}{\\sum_{i=1}^m y_i} \\ln \\left[ m \\frac{y_i}{\\sum_{i=1}^m y_i}\\right] \\right) \\\\\n", " &= \\left[ \\sum_{g=1}^{\\omega} s_{g} \\ln \\left(\\frac{m}{m_g} s_g \\right) \\right] + \\left[ \\sum_{g=1}^{\\omega} s_g \\sum_{i \\in g} s_{i,g} \\ln \\left(m_g s_{i,g}\\right) \\right] \\\\\n", " &= B + W \\\\\n", "\\end{aligned}\n", "$$\n", "\n", "where $s_g = \\frac{\\sum_{i \\in g} y_i}{\\sum_i y_i}$, and $s_{i,g} = y_i / \\sum_{i \\in g} y_i$. \n", "\n", "The first term is the between regions inequality component, and the second is\n", "the within regions inequality component. The within regions term is a weighted\n", "average of inequality between economies belonging to the same region. Similar\n", "to what is done above for the case of interpersonal inequality, the estimate of\n", "the between region (group) component of the decomposition is based on setting\n", "the incomes of all economies (individuals) belonging to a region (group) equal\n", "to that of the regional (group) average of these per capita incomes. Now,\n", "however, intra-regional inequality between economies within the same region is\n", "explicitly considered in the second component.[^weight]\n", "\n", "[^weight]: The regional decomposition does not involve weighting the regions by their respective population. See {cite}`Gluschenko_2018` for further details. \n", "\n", "\n" ] }, { "cell_type": "markdown", "id": "moved-following", "metadata": {}, "source": [ "Once we have covered the decomposition conceptually, the technical implementation is straightforward thanks to the `inequality` package of Pysal, and the `TheilD` class:" ] }, { "cell_type": "code", "execution_count": 40, "id": "funny-paintball", "metadata": {}, "outputs": [], "source": [ "theil_dr = inequality.theil.TheilD(\n", " pci_df[years].values, pci_df.Region\n", ")" ] }, { "cell_type": "markdown", "id": "proved-vatican", "metadata": {}, "source": [ "The `theil_dr` object has the between and within group components stored in the `bg` and `wg` attributes, respectively. For example the \"between\" component for each year is computed is:" ] }, { "cell_type": "code", "execution_count": 41, "id": "floppy-nitrogen", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "text/plain": [ "array([0.00914353, 0.00822696, 0.00782675, 0.00768201, 0.01022634,\n", " 0.0081274 , 0.00783943, 0.00572543, 0.00560271, 0.0054971 ,\n", " 0.00511791, 0.00566001, 0.00486877, 0.00466134, 0.00474425,\n", " 0.00424528, 0.00428434, 0.00453503, 0.00465829, 0.00456699,\n", " 0.00467363, 0.00412391, 0.00366334, 0.00342112, 0.00327131,\n", " 0.00312475, 0.00326071, 0.00359733, 0.00327591, 0.00363014,\n", " 0.00382409, 0.00436261, 0.00399156, 0.00402506, 0.00397 ,\n", " 0.00394649, 0.00353368, 0.00362698, 0.00400508, 0.00449814,\n", " 0.0043533 , 0.00470988, 0.0063954 , 0.00642426, 0.00694236,\n", " 0.00644971, 0.00591871, 0.00554072, 0.00528702])" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "theil_dr.bg" ] }, { "cell_type": "markdown", "id": "headed-native", "metadata": {}, "source": [ "If we store these components in our results table as we have been doing:" ] }, { "cell_type": "code", "execution_count": 42, "id": "alive-brake", "metadata": { "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [], "source": [ "inequalities[\"theil_between\"] = theil_dr.bg\n", "inequalities[\"theil_within\"] = theil_dr.wg" ] }, { "cell_type": "markdown", "id": "portuguese-chance", "metadata": {}, "source": [ "Inference on these decompositions can be done using the `inequality.theil.TheilDSim` class, but we omit that here for brevity and report that, like the Moran's $I$, all of the Theil decompositions are statistically significant. \n", "\n", "Since the within and between components are interpreted as shares of the overall Theil index, we can compute the share of the Theil index due to the between-region inequality." ] }, { "cell_type": "code", "execution_count": 43, "id": "closed-bosnia", "metadata": { "caption": "The share of inequality (measured by the Theil index) that is driven by between-region inequality has generally declined since 1969, although this has rebounded recently." }, "outputs": [], "source": [ "inequalities[\"theil_between_share\"] = (\n", " inequalities[\"theil_between\"] / inequalities[\"theil\"]\n", ")" ] }, { "cell_type": "markdown", "id": "three-wilderness", "metadata": {}, "source": [ "We can visualize the three time series:" ] }, { "cell_type": "code", "execution_count": 44, "id": "fancy-morris", "metadata": { "caption": "Inequality indices (Gini, Theil), shown alongside Moran's I, with the Theil Decomposition into between-region and within-region components at bottom.", "collapsed": false, "ein.hycell": false, "ein.tags": "worksheet-0", "jupyter": { "outputs_hidden": false }, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "inequalities[\n", " [\"theil_between\", \"theil_within\", \"theil_between_share\"]\n", "].plot(subplots=True, figsize=(10, 8));" ] }, { "cell_type": "markdown", "id": "defined-bryan", "metadata": {}, "source": [ " The between-region share of inequality is at its lowest in the mid-2000s, not in the mid-1990s. This suggests that regional differences were very important in the 1970s and 1980s, but this importance has been waning, relative to the inequality *within* US Census Regions. The ratio also generally shares the same pattern, but does not see minima in the same places." ] }, { "cell_type": "markdown", "id": "musical-anderson", "metadata": { "ein.tags": "worksheet-0", "slideshow": { "slide_type": "-" } }, "source": [ "\n", "\n", "\n", "### Spatializing Classic Measures" ] }, { "cell_type": "markdown", "id": "identified-haven", "metadata": {}, "source": [ "While regional decompositions are useful, they do not tell the whole story. Indeed, a \"region\" is just a special kind of group; its \"geography\" is only made manifest through group membership (*is the county \"in\" the region or not?*). This kind of \"place-based\" thinking, while geographic, is not necessarily *spatial*. It does not incorporate the notions of distance or proximity into the study of inequality. The geographical locations of the regions could be re-arranged without impact, so long as the group membership structure is maintained. While, arguably, shuffling regions around means they are no longer \"regions,\" the statistical methods would be no different. \n", "\n", "The final approach we review here is an explicit integration of space within traditional, non-spatial measure. In particular, we consider a *spatialized* version of the Gini coefficient, introduced by {cite}`Rey_2012`. The spatial Gini is designed to consider\n", "the role of spatial adjacency in a decomposition of the traditional Gini. The original index can be formulated focusing on the set of pairwise absolute differences in incomes:\n", "\n", "$$G = \\frac{\\sum_i \\sum_j \\left | y_i - y_j \\right|}{2 n^2 \\bar{y}} $$\n", "\n", "where $n$ is the number of observations, and $\\bar{y}$ is the mean regional income. Focusing on the set of pairwise absolute differences in income, we can de-compose this into the set of differences between \"nearby\" observations and the set of differences among \"distant\" observations. This is the main conceptual point of the \"Spatial Gini\" coefficient. This decomposition works similarly to the regional decomposition of the Theil index:\n", "\n", "$$\n", "\\sum_i \\sum_j \\left |y_i - y_j \\right | =\\sum_i \\sum_j \\underset{\\text{near differences}}{\\left( w_{ij} \\left |y_i - y_j \\right | \\right )} + \\underset{\\text{far differences}}{\\left( (1-w_{ij}) \\left |y_i - y_j \\right | \\right )}\n", "$$\n", "\n", "In this decomposition, $w_{ij}$ is a binary variable that is $1$ when $i$ and $j$ are neighbors, and is zero otherwise. Recalling the spatial weights matrices from [Chapter 4](04_spatial_weights), this can be used directly from a spatial weights matrix.[^sp_gini_ft] Thus, with this decomposition, the Spatial Gini can be stated as\n", "\n", "[^sp_gini_ft]: However, non-binary spatial weights matrices require a correction factor, and are not discussed here.\n", "\n", "$$G = \\frac{\\sum_i \\sum_j w_{i,j}\\left | x_i - x_j \\right|}{2 n^2 \\bar{x}} + \\frac{\\sum_i \\sum_j \\left (1-w_{i,j} )| x_i - x_j \\right|}{2 n^2 \\bar{x}}$$\n", "\n", "with the first term being the component among neighbors and the second term being the component among non-neighbors. The \"spatial Gini\", then, is the first component that describes the differences between nearby observations. \n", "\n", "The spatial Gini allows for a consideration of spatial dependence in inequality. If spatial dependence is very strong and positive, incomes are very similar among nearby observations, so the inequality of \"near\" differences will be small. Most of the inequality in the society will be driven by disparities in income between distant places. In contrast, when dependence is very weak (or even negative), then the two components may equalize. Inference on the spatial Gini can be based on random spatial permutations of the income values, as we have seen elsewhere in this book. This tests whether the distribution of the components are different from that obtained when incomes are randomly distributed across the map. \n", "\n", "The spatial Gini also provides a useful complement to the regional decomposition used in the Theil statistic. The latter does not consider pairwise relationships between observations, while the spatial Gini does. By considering the pairwise relationships between observations, the Gini coefficient is more sensitive, and can also be more strongly affected by small groups of significantly wealthy observations. \n", "\n", "We can estimate spatial Gini coefficients using the `Gini_Spatial` class:" ] }, { "cell_type": "code", "execution_count": 45, "id": "equivalent-china", "metadata": {}, "outputs": [], "source": [ "from inequality.gini import Gini_Spatial" ] }, { "cell_type": "markdown", "id": "pleasant-table", "metadata": {}, "source": [ "First, since the spatial Gini requires binary spatial weights, we will ensure this is so before proceeding:" ] }, { "cell_type": "code", "execution_count": 46, "id": "integrated-smooth", "metadata": {}, "outputs": [], "source": [ "wq.transform = \"B\"" ] }, { "cell_type": "markdown", "id": "sealed-strategy", "metadata": {}, "source": [ "Then, the spatial Gini can be computed from an income vector and the spatial weights describing adjacency among the observations. " ] }, { "cell_type": "code", "execution_count": 47, "id": "complex-reconstruction", "metadata": {}, "outputs": [], "source": [ "gs69 = Gini_Spatial(pci_df[\"1969\"], wq)" ] }, { "cell_type": "markdown", "id": "successful-village", "metadata": {}, "source": [ "The aspatial Gini is stored in the `g` attribute, just like for the aspatial class:" ] }, { "cell_type": "code", "execution_count": 48, "id": "precise-bookmark", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.13556175504269904" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gs69.g" ] }, { "cell_type": "markdown", "id": "muslim-powder", "metadata": {}, "source": [ "The share of the overall Gini coefficient that is due to the \"far\" differences is stored in the `wcg` share:" ] }, { "cell_type": "code", "execution_count": 49, "id": "hawaiian-lexington", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.13541750749645268" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gs69.wcg_share" ] }, { "cell_type": "markdown", "id": "voluntary-gothic", "metadata": {}, "source": [ "The $p$-value for this tests whether the component measuring inequality among neighbors is larger (or smaller) than that would have occurred if incomes were shuffled randomly around the map:" ] }, { "cell_type": "code", "execution_count": 50, "id": "southwest-proxy", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.01" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gs69.p_sim" ] }, { "cell_type": "markdown", "id": "compressed-marker", "metadata": {}, "source": [ "The value is statistically significant for 1969, indicating that inequality between neighboring pairs of counties is different from the inequality between county pairs that are not geographically proximate.\n", "\n", "We can apply the same statistic over each year in the sample using the function-by-column approach as before. In this case, we want to return the statistic itself, as well as the decomposition between variation in the neighbors and that for non-neighbors, and the pseudo P-values:" ] }, { "cell_type": "code", "execution_count": 51, "id": "satisfied-tactics", "metadata": {}, "outputs": [], "source": [ "def gini_spatial_by_col(incomes, weights):\n", " gs = Gini_Spatial(incomes, weights)\n", " denom = 2 * incomes.mean() * weights.n ** 2\n", " near_diffs = gs.wg / denom\n", " far_diffs = gs.wcg / denom\n", " out = pandas.Series(\n", " {\n", " \"gini\": gs.g,\n", " \"near_diffs\": near_diffs,\n", " \"far_diffs\": far_diffs,\n", " \"p_sim\": gs.p_sim,\n", " }\n", " )\n", " return out" ] }, { "cell_type": "markdown", "id": "normal-washington", "metadata": {}, "source": [ "Inference on this estimator is computationally demanding, since the pairwise differences have to be re-computed every permutation, so the following cell takes some time to complete execution: " ] }, { "cell_type": "code", "execution_count": 52, "id": "unknown-suggestion", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1min 43s, sys: 52.8 ms, total: 1min 43s\n", "Wall time: 1min 43s\n" ] } ], "source": [ "%%time\n", "spatial_gini_results = (\n", " pci_df[years].apply(gini_spatial_by_col, weights=wq).T\n", ")" ] }, { "cell_type": "code", "execution_count": 53, "id": "received-bailey", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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gininear_diffsfar_diffsp_sim
19690.1355620.0001440.1354180.01
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" ], "text/plain": [ " gini near_diffs far_diffs p_sim\n", "1969 0.135562 0.000144 0.135418 0.01\n", "1970 0.130076 0.000141 0.129935 0.01\n", "1971 0.128540 0.000142 0.128398 0.01\n", "1972 0.129126 0.000140 0.128985 0.01\n", "1973 0.142166 0.000145 0.142021 0.01" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "spatial_gini_results.head()" ] }, { "cell_type": "markdown", "id": "fabulous-calgary", "metadata": {}, "source": [ "The $p$-values are always small, suggesting that the contribution of the local ties is always smaller than that that would be expected if incomes were distributed randomly in the map.[^near_diffs] We can compute the percent of times the $p$-value is smaller than a threshold using the mean:\n", "\n", "[^near_diffs]: While it is possible that the \"near differences\" component could be *larger* than expected, that would imply negative spatial dependence, which is generally rare in empirical work." ] }, { "cell_type": "code", "execution_count": 54, "id": "intended-thunder", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.0" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(spatial_gini_results.p_sim < 0.05).mean()" ] }, { "cell_type": "markdown", "id": "agreed-metro", "metadata": {}, "source": [ "While it may appear that the component due to \"near differences\" is quite small, this has two reasons. First, the number of \"nearby\" pairs are less than 0.2% of all pairs of observations:" ] }, { "cell_type": "code", "execution_count": 55, "id": "diverse-sherman", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.19385366975502275" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wq.pct_nonzero" ] }, { "cell_type": "markdown", "id": "effective-shelf", "metadata": {}, "source": [ "Second, when spatial dependence is high, nearby observations will be similar. So, each \"near difference\" will also be small. Adding together a small number of small observations will generally be small, relative to the large differences between distant observations. Thus, small values of the \"near\" distances are indicative of spatial dependence. Indeed, we can see visually that as the spatial dependence weakens, the `near_diffs` get larger:" ] }, { "cell_type": "code", "execution_count": 56, "id": "executed-princeton", "metadata": { "caption": "Relationship between the 'near differences' term of the Spatial Gini coefficient and Moran's I. The top, as a measure of spatial dissimilarity, should move in an opposite direction to the bottom, which measures spatial similarity (albeit in a different fashion)." }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "inequalities[\"near_diffs\"] = spatial_gini_results.near_diffs\n", "\n", "inequalities[[\"near_diffs\", \"I\"]].plot.line(\n", " subplots=True, figsize=(15, 6)\n", ");" ] }, { "cell_type": "markdown", "id": "alien-newsletter", "metadata": {}, "source": [ "## Conclusion" ] }, { "cell_type": "markdown", "id": "limiting-strength", "metadata": {}, "source": [ "Inequality is an important social phenomenon, and its geography is a growing concern for social scientists. Geographical disparities in well-being have been pointed to as a major driver behind the rise of right-wing populist movements in the US and Europe {cite}`Rodriguez_Pose_2018`. Thus, understanding the nature of these disparities and their evolution is a challenge for both science and policy.\n", "\n", "This chapter discusses methods to assess inequality, as well as to examine its spatial and regional structure. We have seen the Gini coefficient and Theil index as examples of global measures to summarize the overall level of inequality. As is often the case in many areas of spatial analysis, the straightforward adoption of methods from economics and sociology to spatial data can often be fruitful but, at the same time, can miss key elements of the spatial story. In the context of spatial income disparities, we have highlighted the differences between personal and regional inequality. From this vantage, we have reviewed three approaches to incorporate geography and space in the study of inequality. Together, this gives us a good sense of how inequality manifests geographically, and how it is (possibly) distinct from other kinds of spatial measures, such as those for spatial autocorrelation discussed in chapters [6](06_spatial_autocorrelation) and [7](07_local_autocorrelation). Furthermore, in this chapter we have dipped our toes in spatiotemporal data, exploring how spatial patterns change and evolve over time.\n", "\n", "Before leaving the topic of spatial inequality, we note that there is much more that can be said about inequality and related concepts. Inequality is generally concerned with the static snapshot of the regional income distribution and the shares of that distribution that each region holds. Those shares are reflected in the variance or spread of the distribution. However, this is only one moment of the distribution, and a comprehensive understanding of disparities requires analysis of the distribution's location (mean) and shape (modes, kurtosis, skewness) as well as dispersion. Moreover, movements of individual regions within the distribution over time, or what is referred to as *spatial income mobility* are critical to our understanding of the dynamics of spatial disparities. Full consideration of these concepts is beyond the scope of this chapter. Interested readers are directed to {cite}`Rey2014` as an entry point to these more advanced topics.\n", "\n" ] }, { "cell_type": "markdown", "id": "controlled-conditioning", "metadata": {}, "source": [ "## Questions" ] }, { "cell_type": "markdown", "id": "legendary-emerald", "metadata": {}, "source": [ "\n", "\n", "\n", "1. Why is the study of regional income inequality important? In what ways is the study of regional income inequality different from the study of personal income inequality?\n", "\n", "2. Given that the Theil and Gini statistics appear to have similar time paths, why would a researcher choose to use both measures when analyzing the dynamics of regional disparities? Why not just one one or the other?\n", "\n", "3. What aspects of a regional income distribution are not captured by a Theil or Gini coefficient? Why are these omissions important, and what approaches might be used to address these limitations?\n", "\n", "4. How might the measure of inter-regional income inequality be affected by the choice of the regionalization scheme (i.e., how the different spatial units are grouped to form regions)?\n", "\n", "5. What is the relationship between spatial income inequality and the spatial dependence of regional incomes?\n" ] }, { "cell_type": "markdown", "id": "suspended-barrier", "metadata": {}, "source": [ "## Next Steps\n", "\n", "The literature on regional inequality has exploaded over the last several decades.\n", "For recent reviews of the causes and policy responses see the following: \n", "\n", "\n", "Cörvers, Frank and Ken Mayhew. 2021. \"Regional inequalities: causes and cures.\" *Oxford Review of Economic Policy* 37(1): 1-16.{cite}`corvers2021regional`\n", "\n", "Rodríguez-Pose, Andrés. 2018. \"The revenge of the places that don't matter (and what to do about it).\" *Cambridge Journal of Regions, Economy and Society*, 11(1): 189-20.{cite}`Rodriguez_Pose_2018`\n", "\n", "\n", "Methodologically, spatial analysis of regional disparities is generally covered in two strands of the literature. For work on spatial econometric modeling of convergence and divergence see:\n", "\n", "Arbia, Giuseppe. 2006. *Spatial econometrics: statistical foundations and applications to regional convergence*. Springer Science \\& Business Media.{cite}`arbia2006spatial`\n", "\n", "The second branch of the methodological literature focuses on exploratory spatial data analysis of inequality and is reviewed in:\n", "\n", "Rey, Sergio J. and Julie Le Gallo. 2009. \"Spatial anlaysis of economic convergence.\" In Terry C. Mills and Kerry Patterson (eds.) *Palgrave Handbook of Econometrics*, Palgrave, pages 1251-1290.{cite}`rey2009`" ] } ], "metadata": { "jupytext": { "cell_metadata_json": true, "formats": "ipynb,md" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 5 }