The Cultural Origin of Saving Behaviour Joan Costa Font, LSE Paola Giuliano, UCLA Berkay Ozcan*, LSE
Household Saving Rates Source: OECD National Accounts Statistics: National Accounts at a Glance
Background and Motivation Correlates of differences in household saving rates have been wellstudied: the effect of demographics, differences in income and growth rates, social security systems, tax systems, housing price differentials, financial markets and liberalization Even after controlling for these differences, a large part of variation remains unexplained in cross-national studies.
Background and Motivation One hypothesis is that household savings respond to cultural specific norms. C. D. Carroll, B.K Rhee and C. Rhee, Are There Cultural Effects on Saving? Some Cross- Sectional Evidence. The Quarterly Journal of Economics, 109 (3), 685-699 (1994) - Culture did not matter. - Focused on first generation immigrants in Canada. - Saving rates did NOT vary systematically by their place of origin. - Crude measures of place of origin, i.e. East Asia, Sub-Saharan Africa, Europe, etc. - Wealth from which savings derived was not measured properly.
What we do? We re-examine the hypothesis that culture matters for saving behaviour. Analyse saving behaviour of three generation of immigrants in the UK. Identification strategy relies on the opportunity to observe immigrants in the same environment (the United Kingdom). Distinguishing cultural determinants of savings from factors like tax code, social security system and any other institutional and economic factor. Move beyond first generation: Focus on second and third generation. Alleviates problems of selection and disruption due to immigration experience. Second and third generation are predominantly citizens in the UK, thus no differential institutional environment. Illustrates whether the effects of culture persist and transmitted.
Previous studies on the effects of culture We contribute to the growing number of studies analysing the immigrants behaviour to identify the effect of culture on economic and social outcomes. [i.e.epidemiological Approach] Living arrangements (Giuliano, JEEA 2007) Female labour supply and fertility (Fernandez and Fogli, AEJ 2010, Polavieja ASR 2015) Trust and Preferences for redistribution (Algan and Cahuc, AER 2010) See for a review: Alesina and Giuliano 2015 Journal of Economic Literature All of these studies focused on first and second generations. No study to this date have analysed third generations. Except, Giavazzi et al 2014 on a large set of outcomes on political beliefs on beyond 2 nd generation (using GSS survey which pools third or higher together).
Understanding Society Data A large scale UK household longitudinal survey (~40,000 hhs) collected between 2008-2009 and still ongoing. We used the first 4 waves. Various Advantages: 1. It allows us to identify first, second and third generation immigrants and their country of birth. 2. Large enough to cover various country of origins due to ethnic minority boost sample. 3. Provides rich set of measures on saving behaviour. We have both objective and subjective measures of savings. 4. Large set of wealth and income measures crucial in any analyses of saving behaviour.
Understanding Society Data We use official survey definition for immigrant generation. First generation: Born abroad. Second generation: Those who are born in the UK but with at least one parent not born in the UK; Third generation: Those who are born in the UK to parents both of whom are also born in the UK, but have at least one grandparent, who is not born in the UK. We tried alternative definitions, matriarchal and patriarchal lineages, results do not change. Countries of Origin First Generation Second Generation Third Generation Ireland 261 797 1,299 France 75 46 62 Germany 218 174 144 Italy 84 103 124 Spain 43 25 33 Poland 264 87 137 Cyprus 48 47 103 Turkey 66 16 7 Australia 67 34 27 New Zealand 48 16 6 Canada 48 83 72 US 120 86 79 China/HK 163 60 12 India 901 596 104 Pakistan 784 524 9 Bangladesh 652 276 3 Sri Lanka 204 35 6 Kenya 168 84 14 Ghana 175 47 5 Nigeria 253 104 3 Uganda 84 28 1 South Africa 153 61 31 Jamaica 292 417 90
Specification Y ic is our outcome of interest: Saving Measures X i and X it are time invariant and time variant individual controls including dummies for age and gender X i, marital and employment status, number of children and dummies for different levels of education X it a full set of wave and regional dummies (δ t and μ r ). We also control for permanent income via Altonji and Dorazelski (2005) method in final specifications. Proxy for culture: savings/gdp of the country of origin, from the World Bank s World Development Indicators. Gross domestic savings are calculated as GDP less final consumption expenditures (i.e. total consumption). We pooled data over the 1990 2010 period to minimize measurement error. [Results are robust to different time ranges]
Savings Measures We use three measures of saving behaviour: 1. Total amount of saving: Self-reported monthly amount of savings. Only available for the respondents who answers yes to the propensity to save question below. 2. Propensity to save: Self reported binary measure of saving behaviour, where 1 indicates that an individual answers yes to the following survey question: Do you save any amount of your income, for example by putting something away now and then in a bank, building society, or Post Office account, other than to meet regular bills? Please include share purchase schemes, ISA's and Tessa accounts. 3. Positive Savings: An objective measure of actual savings constructed using wealth variables in the wealth module in waves 2 and 4. Net worth is defined as the sum of housing equity, car equity and liquid financial net worth. We calculated change in net worth from wave 2 to 4. Positive savings, takes the value of the change if the wealth has increased between two time periods or zero if wealth has decreased or stayed the same over the same period. [Net worth(w4) Net worth (w2) ]/ 10000
Descriptive Evidence: Partial correlation plots (Log Amount Saved) 1 China/HK.5 1-1 -.5 0 Ghana Uganda Germany CyprusItaly Jamaica Australia US Poland France Nigeria Kenya Turkey Sri Lanka Pakistan Bangladesh New South Canada Zealand Africa Spain India e( Log (amount saved) X ) Ireland China/HK.5-1 -.5 0 Ghana Uganda Kenya Jamaica Pakistan Sri Lanka Australia New Zealand PolandItaly Germany South Africa India US Turkey NigeriaFrance Cyprus Bangladesh Canada Spain Ireland -.1 0.1.2.3 e( Savings/GDP X ) coef = 3.2502108, (robust) se =.73857977, t = 4.4 -.2 -.1 0.1.2 e( Savings/GDP X ) coef = 2.4411064, (robust) se =.99648093, t = 2.45 First generation immigrants Second generation immigrants Third generation immigrants Note: Log (amount saved) for second generation immigrants is the log of the self-reported monthly amount of saving divided by the net monthly household income. The saving rate in the countries of origin indicates the average gross domestic savings over GDP from 1990-2010.
Results: Log (Amount Saved) Variables 1 st Gen 2 nd Gen 3 rd Gen 1 st Gen (b) 2 nd Gen (b) 3 rd Gen (b) Dom. savings/gdp 1.520** 1.184** 0.849* 1.634** 1.665*** 0.772 (2.782) (2.287) (1.796) (2.797) (2.914) (1.584) Control Variables Sex, Marital Status, Education, Soc Class, Employment status, Fathers education, All age dummies All All All All All All Region and Wave Dummies Region x Wave interactions
Findings Immigrants coming from countries with high saving rates also tend to save more in the United Kingdom The coefficients are not only statistically significant, but they are also meaningful in magnitude. 1 st dev. change in the country of origin savings rate is associated with an increase of saving rates of.051 standard deviations in the first generation,.040 standard deviation in the second generation..025 standard deviation in the third The impact seems to be declining across generations. The effect is also meaningful when compared to other economic factors such as the level of education: for the first generation, the effect of savings in the country of origin is equal to 41% of the effect of having a college degree (for which the beta coefficient is equal to 0.104), 51% of the effect of income.
Positive Savings: Amount of increase in wealth between Wave 2 and 4 VARIABLES 1st Gen 2nd Gen 3rd Gen 1st Gen (b) 2nd Gen (b) 3rd Gen (b) Dom. savings/gdp 12.538* 27.430** 16.742** 6.459* 36.240*** 13.352** (6.723) (9.817) (6.354) (3.676) (12.588) (5.708) Control Variables YES YES YES YES YES YES Age dummies YES YES YES YES YES YES Region and Wave Dummies YES YES YES YES YES YES Region Wave Interactions YES YES YES
Probit estimates of Able to Save VARIABLES 1 st Gen 2 nd Gen 3 rd Gen 1 st Gen (b) 2 nd Gen (b) 3 rd Gen (b) Dom. savings/gdp 0.295** 0.274** 0.236** 0.326** 0.307* 0.220** -0.123 (0.126) (0.120) (0.130) (0.159) (0.109) Control Variables YES YES YES YES YES YES Age dummies YES YES YES YES YES YES Region and Wave Dummies YES YES YES YES YES YES Region Wave Interactions YES YES YES
Conclusions We find robust association between immigrant saving behaviour and the saving rates in their country of origin. The association persists up to the third generation. Our results are consistent across three different measures. The results go against the existing evidence and highlight the importance of thinking about cultural factors when considering policies about savings and dissavings.
Thank you
First Generation Second Generation Third Generation Obs. Mean St. dev Obs. Mean St. dev Obs. Mean St. dev Log Amount Saved 5,171 1.327 2.249 3,746 1.832 2.451 2,371 1.865 2.422 Dom Savings/GDP 5,171 0.200 0.075 3,746 0.224 0.082 2,371 0.280 0.071 Saves 5,138 0.278 0.448 3,741 0.383 0.486 2,363 0.398 0.490 Positive Savings 3,330 3.857 27.614 2,637 4.560 62.258 1,843 3.709 24.621 Female 5,171 0.531 0.499 3,746 0.568 0.495 2,371 0.577 0.494 Married 5,171 0.642 0.480 3,746 0.436 0.496 2,371 0.461 0.499 Number of Children 5,171 0.975 1.222 3,746 0.841 1.146 2,371 0.608 0.978 Log Monthly Income 5,171 9.719 0.110 3,746 9.727 0.117 2,371 9.717 0.140 College and above 5,171 0.328 0.470 3,746 0.299 0.458 2,371 0.261 0.439 Other higher degree 5,171 0.101 0.301 3,746 0.125 0.331 2,371 0.117 0.321 A-Level degree 5,171 0.148 0.355 3,746 0.238 0.426 2,371 0.229 0.420 Secondary education 5,171 0.131 0.338 3,746 0.202 0.402 2,371 0.188 0.391 Unemployed 5,171 0.072 0.259 3,746 0.093 0.291 2,371 0.057 0.233 Out of the labor force 5,171 0.411 0.492 3,746 0.333 0.471 2,371 0.386 0.487 Father left school with no qualification 3,812 0.268 0.443 2,616 0.381 0.486 1,973 0.397 0.489 Father some qualification 3,812 0.269 0.444 2,616 0.253 0.435 1,973 0.200 0.400 Father post-school qualification 3,812 0.164 0.370 2,616 0.178 0.382 1,973 0.278 0.448 Father university or higher degree 3,812 0.193 0.395 2,616 0.126 0.332 1,973 0.119 0.324 Large employers & higher management 5,171 0.017 0.130 3,746 0.029 0.167 2,371 0.035 0.184 Higher professional 5,171 0.058 0.234 3,746 0.058 0.235 2,371 0.050 0.218 Lower management & professional 5,171 0.126 0.332 3,746 0.180 0.384 2,371 0.190 0.393 Intermediate 5,171 0.063 0.242 3,746 0.104 0.305 2,371 0.079 0.270 Small employers 5,171 0.057 0.232 3,746 0.053 0.224 2,371 0.052 0.222 Lower supervisory & technical 5,171 0.032 0.176 3,746 0.032 0.175 2,371 0.045 0.207 Semi-routine 5,171 0.123 0.328 3,746 0.115 0.319 2,371 0.090 0.287 Routine 5,171 0.070 0.255 3,746 0.044 0.204 2,371 0.051 0.219