Significance of Intergenerational Economic Mobility - Essay Example

Intergenerational Mobility Your name: Institution name: Significance of intergenerational economic mobility? (Solon, 1992). In other words, Intergenerational economic mobility can be defined as a change in social position that occurs over multiple generations (Blanden, Goodman, Gregg, and Machin, 2004). This is found to be social mobility of children in relation to their parents (Lee and Gary, 2009). For example, adult’s children are likely to be part of the same income category or occupational category as their parents. The significant of intergenerational economic mobility is that is often used as a measure of the importance of merit rather than political influence, prejudice and other similar considerations in determining the success and failure in a country (Blanden, Goodman, Gregg, and Machin, 2004). Although it can be related to the importance of merit in determining the success, the connection has been noted to be more complex (Solon, 1992). A research study for the OECD have noted reasons why intergenerational economic mobility is important: 1) the ways country resources are allocated across generations today have been noted to influence economic welfare for generations (Lee and Gary, 2009). Secondly, (Blanden, Goodman, Gregg, and Machin, 2004). particular country will (Atkinson, Maynard, and Trinder, 2009). And lastly, when income mobility is improved, it may be a way of achieving greater economic efficiency (Blanden, Gregg and Macmillan, 2007), in that those talents of individual from disadvantaged backgrounds are put into good use. (Lee and Gary, 2009). or associated with their parental income (Solon, 1992). What are the major challenges for empirical research? Demanding data requirements is seen to make accuracy calculating intergenerational mobility to be difficult. A researcher would have a comprehensive data on both the on the incomes of children when they have grown up and the incomes of children’s parents (Hertz, 2007). Large data-set that contains intergenerational personal-level income data have already been developed from census and taxation data in Canada and Nordic countries (Anna, 2007). However, in most developing nations such data is not available (Atkinson, Maynard, and Trinder, 2009). In the U.S, Britain and Germany, intergenerational mobility research studies have usually used a panel data on the income of children when they are grown up and no longer staying with their parents, and incomes of their parents (Hertz, 2007). However, few research studies have able to collect data on people’s economic situations for a long period of time. Since relying on individual’s recollection of their parents’ income is seen with difficulties (Belley and Lance, 2007), sometimes research (Lee and Gary, 2009). However, calculating income data using these tool variables will inflate estimates as compared to employing actual income data (Belley and Lance, 2007), especially when only one year or two years or three years income data on the attributes is used to predict income, such as educational levels of parents, and is seen to have an independent effect on the children’s outcomes (Hertz, 2007). Just employing finely grained occupation data to predict income of people have been able to produce estimates that are considerably different from results based on detailed national income datasets (Blanden, Goodman, Gregg, and Machin, 2004). Using social social and economic status data that are based on the economic returns for different jobs will generate similar intergenerational mobility results to self-reported income, although sometimes estimates are found to be lower (Lee and Gary, 2009). For some individual’s social and economic status may be better capture their long term economic position than the current income (Blanden, Gregg and Macmillan, 2007). However, the limitation is inputting a person’s economic situation on the basis of their career or employment. Even when the data on income is made available, life cycle effects on individual’s incomes are used accurately to measure individual economic situations difficulties (Atkinson, Maynard, and Trinder, 2009). This is because some types of employees, particularly those employees who earn higher salaries, they will tend to reach their peak earning few years than other employees. While the entry of highly educated people into the labour market is often delayed by the time they finished learning or finished their educations, on average they subsequently enjoy higher earnings than those people who are found to possess lower educational qualifications (Lee and Gary, 2009). Measuring incomes mobility when individual are in their forties’ or fifth’s is also likely to be measured inaccurately their permanent income because individuals in this age group their real wages or salaries is seen to decline at this age (Atkinson, Maynard, and Trinder, 2009). As a result of life cycle biases, estimates of intergenerational mobility in some countries are found to be sensitive to the age group at which real earning is observed. The income of children and that of their parents should be normally be measured between their mid-forties and early thirties, when their income is likely to reflect their life time earnings and permanent income (Belley and Lance, 2007). In addition, because individual’s incomes often is seen to vary year to years in response to transitory short term factors, income measure from a few period of time tend to produce “snapshot” that are poorly capture individual’s permanent or life time income (Hertz, 2007). In other words, researchers may like to use long term data on incomes of families, only a few measurements are available (Blanden, Goodman, Gregg, and Machin, 2004). The errors in variables bias depresses measures of intergenerational economic mobility because each income that is observed is seen to contain a random component, and only small number of income can mask the relationship between children income and the incomes of their parents (Lee and Gary, 2009). Accurate intergenerational economic mobility results has been seen to occur in most countries when a large number of measurements are available (Blanden, Gregg and Macmillan, 2007). However in countries such as Norway, additional years of income data is seen to have little or no effect. The accuracy of the data and sample selection rules have also been seen to be important. For example, intergenerational mobility results have been found to be affected by the exclusion or inclusion of part-time and unemployed workers (Belley and Lance, 2007). When total income is inflated estimates of immobility in Canada and the US when compared to just using labor market earnings, but data from this effect are unavailable for most nations particularly in developed nations (Lee and Gary, 2009). Sometimes, data that is used on income is seen to omit those people who are dependent on benefit (Blanden, Gregg and Macmillan, 2007). Intergenerational mobility results that employ the datasets may not be used to those individual who grew up with parents who are unemployed. For example, estimates of intergenerational earnings mobility in the US and Canada is seen to exclude families that come from lowest decile of family because this group of people is seen to contain few employees who are included in Canadian tax bracket (Hertz, 2007). There are incentives for individuals to under report their taxable income. In addition, using income data that is self-reported can lead to errors that have resulted in inaccurate recall, while using bands to collect data results in further imprecision (Belley and Lance, 2007). What persons earn is also seen to be a private matter, and non-response rates survey research questions about income is seen to be relatively high. Rates of intergenerational mobility in a nation can also change with time. Also, research studies into intergenerational mobility have often covered just men and their fathers, and not women and their mothers or women and their fathers, when to be comprehensive and representative, research study should include both women and men. Although fathers’ income is seen to be more stable, with women or mother reducing their working hours to have time to look for their children, research should test this effect on the total family income as well as those incomes for fathers. Similarly, employing total family income as dependent variable is desirable. For example, in some countries the number of grown up children in families is seen to affect the results. Studies that use large assets have also shown that rate of intergenerational mobility is seen to sometime vary across the income distribution and the mobility will sometimes vary in income distribution, and mobility is seen at its lowest near the extremes of the income distribution (Corak and Heisz, 1999). Due to this effect, modelling of intergenerational mobility as a linear relationship will sometimes produce imprecise results. The mechanism of which economic conditions of different families affect the incomes of their children have also been found to be unclear (Lee and Gary, 2009). In addition, in some cases only small proportion of variation in individual’s income can be explained by what parent earned , this suggest that other variable are seen to be important. Indeed, Australia and New Zealand studies have shown that people specific factors, such as child poverty and coming from poor families or dysfunctional home environment are seen to have a modest effect on the outcomes for people (Corak and Heisz, 1999). Many disadvantages are seen to be associated strongly with negative outcomes, but a lot of people have been reported to overcome them. Protective factors that include person characteristics, good parenting, family cohesion and warmth, and external support systems. . Reference List Anna Cristina d’Addio 2007, Intergenerational Transmission of Disadvantage: Mobility or Immobility Across Generations? A Review of the Evidence for OECD Countries, OECD Social, Employment and Migration Working Paper No. 52 Blanden, J., A. Goodman, P.Gregg, and S. Machin. 2004. “Changes in Intergenerational Mobility in Britain,”in M. Corak (ed.):Generational Income Mobility in North America and Europe. Cambridge: Cambridge University Press Hertz, Tom. 2007. “Trends in the Intergenerational Elasticity of Family Income in the United States , ” Industrial Relations 46:22 -50. Lee, Chul-In and Gary Solon. 2009. “Trends in Intergenerational Income Mobility,” Review of Economics and Statistics 91:766-772. Atkinson, A.B., A.K. Maynard, and C.G. Trinder (2009).Parents and Children: Incomes in Two Generations . London: Heinemann Educational Books Belley, Philippe and Lance Lochner (2007). “The Changing Role of Family Income and Ability in Determining Educational Attainment.” NBER Working Paper 13527. Solon, G. (1992) "Intergenerational Income Mobility in the United States" American Economic Review, 82(3), 393‐408. Corak, M. and A. Heisz (1999) “The intergenerational earnings and income mobility of Canadian men: Evidence from longitudinal income tax data” Journal of Human Resources, 34(3), 504‐533. Blanden, J., P. Gregg and L. Macmillan (2007) “Accounting for Intergenerational Income Persistence: Noncognitive Skills, Ability and Education” Economic Journal, 117(519), C43‐C60. Lee, C.I. and G. Solon (2009) "Trends in Intergenerational Income Mobility" Review of Economics and Statistics, 91(4), 766‐772. George J. Borjas. (2006). Making It In America: Social Mobility in the Immigrant Population Fall. Read More