NBER WORKING PAPER SERIES
CAPITAL MARKETS IN CHINA AND BRITAIN, 18TH AND 19TH CENTURY: EVIDENCE FROM GRAIN PRICES
Wolfgang Keller Carol H. Shiue Xin Wang
Working Paper 21349 http://www.nber.org/papers/w21349
NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 July 2015
We thank Howard Bodenhorn, Stephen Broadberry, Edmund Cannon, Kris Mitchener, Kevin O’Rourke, Sevket Pamuk, and Jeff Williamson, as well as seminar participants at CEPR/CAGE Venice conference for comments. Thanks to Edmund Cannon, Wang Yeh-Chien, and Nathan Nunn for help with data. William Ridley and Austin Smith performed excellent research assistance. NSF support under grant SES 1124426 is gratefully acknowledged. Part of this research was done when Keller and Shiue were National Fellows at the Hoover Institution in Stanford, which they thank for its hospitality. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
NBER working papers are circulated for discussion and comment purposes. They have not been peer- reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
© 2015 by Wolfgang Keller, Carol H. Shiue, and Xin Wang. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Capital Markets in China and Britain, 18th and 19th Century: Evidence from Grain Prices Wolfgang Keller, Carol H. Shiue, and Xin Wang NBER Working Paper No. 21349 July 2015 JEL No. G12,N10,N13,N25,O10
ABSTRACT
Capital markets allow surplus income to be invested into productivity-enhancing projects. Despite their prominence in general accounts of growth little is known on their role in the emergence of modern economic growth. In this paper we ask whether capital market performance might explain why Britain surged ahead of China in the 18th century. We employ an asset-pricing model together with information on regional grain prices to derive interest rates, and then compare capital market development in large parts of Britain and China. We first calibrate the method and show that it can replicate key features of the United States’ early 19th century capital market, where more systematic data from bank interest rates is available. Using this approach we estimate interest rates for Britain that are at least 20% lower than those for China, for the years 1770 - 1860. Moreover, the regional integration of British capital markets, measured in terms of bilateral interest rate correlations, was far greater than it was in China. The Yangzi Delta correlations come close to the British average at distances below 200 kilometers, but at larger distances interest rate correlations in Britain are twice those of the Delta, and three or more times as high as elsewhere in China. We also find that Britain’s advantage over China in terms of market integration existed already in the late 18th century. Backcasting on the 19th century trends suggests capital market divergence started by the year 1690. Overall, our results provide support for the hypothesis that divergence in capital market development occurred before income divergence, and may therefore be an important factor in explaining the Great Divergence.
Wolfgang Keller Xin Wang Department of Economics University of Colorado Boulder University of Colorado-Boulder Room 307, Economics Building Boulder, CO 80309-0256 256 UCB and Stanford University, Hoover Institution Boulder, CO 80309-0256 and also NBER [email protected] [email protected]
Carol H. Shiue University of Colorado Department of Economics Boulder, CO 80309 and Stanford University Hoover Institution and also NBER [email protected] !"#!$%&'()*%+'$#
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(A1!FB06(9!E2CEB1H0G6BAhX! 5(A45(6!F525H6!82QH2RH(A!05H)(AF52X! ! ! xw! ! xx! # ! xy! Table 1. United States Regional Interest Rates, 1815 – 1859 Year New York City Philadelphia Richmond New Orleans Indianapolis 1815 4.62 1816 5.70 1817 3.69 1818 5.55 1819 3.84 1820 5.60 1821 4.78 1822 5.65 4.08 1823 3.42 3.81 1824 5.21 4.14 1825 4.24 4.61 1826 5.86 3.97 1827 4.95 4.97 1828 5.82 3.97 1829 4.58 4.23 1830 4.97 4.45 1831 5.15 4.84 1832 4.48 6.28 1833 5.03 6.54 8.02 1834 5.69 3.41 3.75 6.82 1835 5.11 6.12 4.43 7.54 7.97 1836 6.82 5.74 7.22 7.16 7.60 1837 5.91 4.75 5.70 11.28 8.50 1838 5.33 5.47 4.41 7.68 8.35 1839 4.24 3.44 6.78 10.15 1840 5.57 5.73 5.43 9.01 1841 5.27 4.41 4.21 8.86 7.65 1842 3.95 2.50 4.20 8.85 5.05 1843 5.37 3.72 4.12 2.85 1844 5.80 5.18 4.15 5.74 1845 5.21 4.20 5.10 7.86 1846 4.69 6.39 3.95 1847 5.04 5.21 4.99 6.32 1848 5.32 4.83 4.43 7.73 8.36 1849 7.17 6.35 4.19 4.84 7.77 1850 5.62 6.47 4.53 7.42 9.45 1851 6.32 4.69 4.72 7.79 5.95 1852 7.23 5.56 5.53 7.91 6.81 1853 4.99 5.10 4.46 7.38 6.37 1854 4.98 5.31 5.04 8.50 7.70 1855 5.87 5.70 5.18 12.81 10.89 1856 6.09 4.45 4.29 9.25 1857 5.45 3.16 3.88 1858 4.95 6.46 2.92 1859 4.62 4.32 5.96 Source: Bodenhorn and Rokoff (1992) Table 2. Calibration Observed Asset-pricing grain storage model Christiano- Unfiltered Moving Average Baxter-King Fitzgerald Butterworth (1) (2) (3) (4) (5) (6) Panel A: Interest rate levels Mean 0.058 0.074 0.269 0.197 0.127 0.029 (0.018) (0.507) (1.802) (1.113) (0.337) (0.241) Panel B: Interest rates over time T-statistic of regression on observed interest rate Mean 1.63 1.05 1.98 1.91 2.17 (1.40) (1.52) (0.65) (0.46) (0.57) Panel C: Capital market integration Bilateral interest rate correlations Mean 0.25 0.73 0.80 0.72 0.54 0.46 (0.33) (0.16) (0.09) (0.15) (0.28) (0.30) Correlation w/ column (1) 0.72 0.61 0.75 0.69 0.72 Notes: Observed are interest rates from Bodenhorn and Rokoff (1992); all other are based on grain price changes, computed as the average of log month-to-month changes from August to December. Unfiltered: no adjustment to grain prices; Moving average (MA) using 2 lags, the month itself, and 2 leads; Baxter-King (BK) filters below 4 months, above 12 months, moving average of order 10; Cristiano-Fitzgerald (CF) filters below 3 months, above 12 months; Butterworth (BW) filters below 3 months (order 8), and above 12 months (order 2). Standard deviation in parentheses. Table 3. Summary statistics for grain prices One-month ∆ non-zero n Mean Std. Dev. Coeff. Var. Mean Britain Wheat 48,314 7.732 2.696 0.349 0.994 Bandpass filtered Wheat 48,314 1.001 0.049 0.048 0.994 China Wheat 107,069 1.466 0.521 0.355 0.344 Millet 52,947 1.601 0.558 0.348 0.456 Rice 1st quality 74,282 1.798 0.603 0.336 0.517 Rice 2nd quality 84,458 1.694 0.572 0.338 0.464 Bandpass filtered Wheat 107,069 1.000 0.020 0.020 0.344 Millet 52,947 1.000 0.022 0.022 0.456 Rice 1st quality 74,231 1.000 0.018 0.018 0.517 Rice 2nd quality 84,374 1.000 0.020 0.020 0.464 Notes: Source of data, see text. Table 4. Carry costs of grain, 1770 to 1860 Monthly rate Annualized n Mean (%) Std. dev. (%) Britain Wheat 4,074 0.854 2.577 10.248 China All grains 15,152 1.144 2.446 13.732 Britain Wheat 4,074 0.854 2.577 10.248 China Wheat 4,930 1.124 2.577 13.488 China Millet 3,973 1.020 2.598 12.242 Rice 1st quality 5,135 1.071 1.978 12.854 Rice 2nd quality 5,384 1.074 2.133 12.883 Band-pass filtered Britain Wheat 4,102 0.684 2.239 8.209 China All grains 13,403 0.801 2.172 9.612 Britain Wheat 4,102 0.684 2.239 8.209 China Wheat 4,221 0.774 1.886 9.284 China Millet 3,314 0.684 2.000 8.210 Rice 1st quality 4,366 0.761 2.048 9.131 Rice 2nd quality 4,794 0.781 2.054 9.376 Table 5. From carry costs to interest rates: the role of storage, trade, and harvest patterns Interest rate Carry costs Interest rate broad Adjustments Climate Climate & Climate & Climate & Waterway Waterway & Waterway & Harvest Patterns Harvest Patterns (1) (2) (3) (4) (5) Panel A. Unfiltered data Mean in % 10.248 5.271 5.348 5.348 5.348 Britain (30.924) (30.804) (30.795) (30.795) (30.795) n 4,074 4,074 4,074 4,074 4,074 Mean in % 13.732 9.374 9.440 9.200 6.258 China (29.350) (29.040) (29.088) (29.077) (24.544) n 15,152 15,152 15,152 15,152 18,586 Panel B. Bandpass-filtered data Mean in % 8.209 4.891 5.415 5.415 3.204 Britain (26.868) (26.808) (26.772) (26.772) (15.684) n 4,102 4,102 4,102 4,102 4,115 Mean in % 9.612 7.616 7.482 7.501 4.023 China (26.064) (25.800) (25.934) (25.814) (15.946) n 13,403 13,403 13,403 13,403 19,736 Notes: Standard deviation in parentheses Table 6. Bilateral interest rate correlations and geographic distance I Based on unfiltered price data Britain China Wheat Wheat Rice 1st quality Rice 2nd quality Millet 0-100km 0.80 0.53 0.65 0.56 0.54 (0.16) (0.38) (1.18) (0.62) (0.36) [n = 350] [n = 186] [n=196] [n=202] [n=152] 100-200km 0.77 0.41 0.45 0.40 0.44 (0.16) (0.55) (1.37) (0.69) (0.38) [n = 788] [n = 566] [n=602] [n=628] [n=484] 200-300km 0.74 0.30 0.39 0.36 0.35 (0.17) (0.43) (1.43) (0.72) (0.45) [n = 720] [n=730] [n=758] [n=840] [n=616] 300-400km 0.73 0.21 0.20 0.22 0.25 (0.18) (0.39) (0.80) (1.01) (0.43) [n = 476] [n=786] [n=802] [n=902] [n=684] 400-500km 0.70 0.11 0.20 0.14 0.17 (0.18) (0.49) (2.07) (0.88) (0.38) [n = 246] [n = 886] [n=908] [n=1,108] [n=568] 500-600km 0.70 0.07 0.11 0.11 0.12 (0.19) (0.48) (2.04) (1.22] (0.27) [n = 64] [n=1,002] [n=1,018] (n=1,184) [n=548] Notes: Entries are average correlations over period 1770 to 1860. Interest rates as underlying Table 5, Panel A, column 4. Standard deviations in parentheses. Table 7. Bilateral interest rate correlations and geographic distance II Based on filtered price data Britain China Wheat Wheat Rice 1st quality Rice 2nd quality Millet 0-100km 0.71 0.35 0.44 0.51 0.29 (0.17) (0.28) (0.50) (0.46) (0.34) [n = 350] [n = 138] [n=166] [n=158] [n=134] 100-200km 0.68 0.26 0.34 0.35 0.24 (0.18) (0.30) (0.56) (0.54) (0.35) [n = 788] [n = 424] [n=500] [n=494] [n=390] 200-300km 0.66 0.21 0.23 0.25 0.16 (0.17) (0.33) (0.62) (0.58) (0.35) [n = 720] [n=556] [n=620] [n=612] [n=482] 300-400km 0.65 0.13 0.16 0.17 0.12 (0.16) (0.31) (0.73) (0.56) (0.34) [n = 476] [n=560] [n=628] [n=660] [n=514] 400-500km 0.63 0.10 0.15 0.10 0.07 (0.19) (0.34) (0.78) (0.55) (0.33) [n = 246] [n = 630] [n=658] [n=804] [n=398] 500-600km 0.62 0.07 0.07 0.08 0.03 (0.23) (0.34) (0.75) (0.62] (0.29) [n = 64] [n=706] [n=682] (n=802) [n=374] Notes: Entries are average correlations over period 1770 to 1860. Interest rates as underlying Table 5, Panel A, column 4. Standard deviations in parentheses. Table 8. Interest Rate Correlations: Inside the Yangzi Delta and beyond Distance 0-100km 100-200km 200-300km Britain Mean 0.621 0.592 0.552 n 350 788 720 Yangzi Delta Rice Mean 0.598 0.618 0.300 n 36 28 20 Yangzi Delta All Grains Mean 0.468 0.242 0.115 n 66 68 36 China outside Yangzi Delta, Mean 0.416 0.238 0.086 All Grains n 704 2,364 3,194 Notes: Interest rates based on time-series filtered data (Table 5, Panel B, column 5). Yangzi Delta are bilateral correlations between nine particular prefectures located in Zhejiang and Jiangsu province, see the appendix. Rice is first-grade and second-grade rice. All Grains is rice plus wheat. Figure 1. Price behavior in a model with storage 104 Storage = 0 102 ) t P 100 Price ( 98 Storage = max 96 0 3 6 9 12 15 18 21 24 Period Source: Based on Williams and Wright (1991). Figure 2. Philadelphia Wheat Price, 1836 to 1840 10.00 9.00 8.00 7.00 6.00 5.00 4.00 3.00 Price per bushel of wheat ($) 2.00 1.00 0.00 Jul-1837 Jul-1836 Jul-1839 Jul-1838 Jul-1840 Jan-1837 Sep-1837 Jan-1836 Jan-1839 Sep-1836 Sep-1839 Jan-1838 Sep-1838 Jan-1840 Sep-1840 Nov-1837 Mar-1837 Nov-1836 Nov-1839 Nov-1838 Mar-1836 Mar-1839 Nov-1840 Mar-1838 May-1837 Mar-1840 May-1836 May-1839 May-1838 May-1840 Source: Jacks (2006). Figure 3. Filtered versus unfiltered Philadelphia wheat prices, 1836-40 2.40 0.15 2.20 0.1 2.00 0.05 1.80 0 1.60 -0.05 log price per bushel 1.40 -0.1 1.20 Butterworth-filtered log price per bushel 1.00 -0.15 Jul-1837 Jul-1836 Jul-1839 Jul-1838 Jul-1840 Jan-1837 Sep-1837 Jan-1836 Jan-1839 Sep-1836 Sep-1839 Jan-1838 Sep-1838 Jan-1840 Sep-1840 Nov-1837 Mar-1837 Nov-1836 Nov-1839 Nov-1838 Mar-1836 Mar-1839 May-1837 Nov-1840 Mar-1838 Mar-1840 May-1836 May-1839 May-1838 May-1840 Unfiltered Butterworth band-pass filtered Source: Jacks (2006) and own calculations Figure 4. Interest rate estimates in 19th Century United States Average per year, 1835 to 1855 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 New York City Philadelphia Bank interest rates Grain price & storage model Source: Own calculations (Table 2), and Bodenhorn and Rokoff (1992). Figure 5. Monthly wheat price in Bedfordshire county, 1828 – 1860 14 12 10 8 6 Shillings per bushel 4 2 0 Source: Data from the London Gazette. Figure 6. Monthly price of first-grade rice, Guilin prefecture, 1828 - 1860 1.45 1.4 1.35 1.3 1.25 1.2 Taels per shi 1.15 1.1 1.05 1 Source: Chinese Academy of Social Sciences (2009) Figure 7. Sample size in terms of numbers of regions 250 200 150 100 50 0 1770s 1780s 1790s 1800s 1810s 1820s 1830s 1840s 1850-60 Number of Chinese prefectures Number of British counties Figure 8. Climate in China: Annual wetness, 1770 - 1860 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 1772 1774 1776 1797 1812 1814 1816 1795 1778 1770 1793 1818 1799 1810 1801 1782 1784 1786 1790 1852 1854 1856 1788 1832 1780 1834 1822 1836 1842 1824 1826 1858 1844 1846 1850 1805 1838 1828 1848 1830 1803 1820 1840 1860 1808 Mean wetness Standard deviation of wetness Source: State Meteorological Society (1981) Figure 9. Climate in Britain: Annual rainfall, 1770 to 1860 6 5 4 3 2 1 0 1772 1774 1776 1812 1814 1816 1778 1770 1818 1792 1794 1796 1810 1782 1784 1786 1798 1790 1852 1854 1856 1788 1832 1780 1834 1822 1836 1824 1842 1826 1858 1844 1846 1850 1838 1828 1848 1830 1802 1820 1840 1804 1860 1806 1808 1800 Mean rainfall Standard deviation of rainfall Source: Pauling, Luterbacher, Casty, and Wanner (2006) Figure 10. Interest rates over time, 1770 to 1860 0.12 0.1 0.08 0.06 0.04 Average annual interest rate 0.02 0 Britain China Source: Own calculations (Table 5, Panel B, column 4) Figure 11. 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L0++%&'&E 1) L-#8-6?/'/0.& 11 L-#?$-8&.('/0.& 13 M-.,-%2 15 M-.?/78I?-#'/0.& 1; M-.?/68<&.%7#+ 1= M-??0#$/78'/0.& 1> NE,-.+'/0.& 19 O&8<.-2&'/0.& 3@ P7+#-.'/0.& 3! P6?%7#+ 3) Q/.-I'/0.& 31 Q-8&.'&? 33 Q?7,,-.+'/0.& 35 Q6,,-%2 3; Q6..&( 3= Q6''&E 3> R7.A042'/0.& 39 R&'?8-.%7#+ 5@ R0%?'/0.& 5! R-.4&'?&.'/0.& 5) S-.2'/0.& Table C. Spatial Aggregation and interest rate correlations in Britain Baseline Aggregated Unfiltered Filtered Unfiltered Filtered 0-100 km 0.80 0.71 0.85 0.81 (0.16) (0.17) (0.10) (0.11) [n = 350] [n = 350] [n = 42] [n = 42] 100-200km 0.77 0.68 0.82 0.74 (0.16) (0.18) (0.13) (0.13) [n = 788] [n = 788] [n = 162] [n = 162] 200-300km 0.74 0.66 0.81 0.71 (0.17) (0.17) (0.12) (0.11) [n = 720] [n = 720] [n = 170] [n = 170] 300-400km 0.73 0.65 0.80 0.70 (0.18) (0.16) (0.12) (0.11) [n = 476] [n = 476] [n = 132] [n = 132] 400-500km 0.70 0.63 0.78 0.69 (0.18) (0.19) (0.13) (0.11) [n = 246] [n = 246] [n = 74] [n = 74] 500-600km 0.70 0.62 0.79 0.67 (0.19) (0.23) (0.19) (0.15) [n = 64] [n = 64] [n = 20] [n = 20] Notes: All results are for Britain. Shown in the Baseline columns are results for 52 counties. In the Aggregated columns, the 52 counties are aggregated to 26 regions that on average closely resemble the size of a Chinese prefecture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ean interest rate correlation 0.1 0 < 100 100 - 200 200 - 300 300 - 400 400 - 500 -0.1 Distance (kilometers) Britain narrow Britain broad China narrow China broad