favorable (picking winners), or to the opposite, in order to curb regional inequality. The narrative suggests that a picking-the-winner strategy may have been especially important in the first stage of the reforms, when all SEZ were chosen along the coast and close to potential trading partners and investors such as Hong Kong and Taiwan. Ideally, one would like to have instruments to isolate exogenous sources of variation in the reform treatment, but finding valid instruments is difficult in practice. We mitigate the concern with endogeneity through three complementary strategies. First, we restrict the sample to cities located in inland provinces where the selection of the zones was largely based on a rigid administrative criterion, i.e., being a provincial capital. Second, we augment the regressions with indicators for the immediate pre-reform years to capture differential trends. Third, we control for flexible differential trends depending on the initial conditions of the different cities. This is potentially important, since the cities hosting SEZ are on average more densely populated and more developed than those that did not host SEZ. The results are reassuring: the effect of SEZ is robust in the restricted sample, differentials before the actual establishment of the zone are insignificant, and allowing for differential trends based on the initial development or population density does not significantly affect the coefficients of interest.
Using the calibrated parameters, we first predict the gender hours ratio for 1990. Then we consider three different counterfactuals along with the baseline in producing the estimates for 2016. These counterfactuals reflect three forces that are potentially responsible for the slowdown in the gender hours ratio since 1990: the emergence of service offshoring, the weakening of structural transformation towards the service sector, and the lower pace of diminishing gender discrimination. The baseline contains all these elements and we change one corresponding mechanism for each counterfactual. Using the forecasts of the baseline and counterfactuals in 2016, we compute changes in the gender hours ratio from the prediction for 1990. We measure the contribution of each counterfactual by how much of the change in the gender hours ratio is reduced in the baseline compared to the change for each counterfactual. The first counterfactual considers the possibility that the trend for service offshoring be- tween 1970 and 1990 has been the same since 1990. Since we adopt a simplifying assumption that there was no service offshoring in 1970 and 1990, this scenario hypothesizes that service offshoring did not appear until 2016. We impose K s,1 = K s,2 = 1 to enforce this counter-
As there are three shocks in this model, physical capital technology shock, human capital technology shock and money shock, the maximum number of observable variables is three. When the rank of policy function matrix is less than the number of observables, there will be the stochastic singularity problem. In order to estimate the system for the US economy, I have used three macroeconomic observables at quarterly frequency. Following the previous study by Smet and Wouters (2007), this chapter includes real GDP, real government spending, and the GDP deflator. The real variables are obtained by deflating their nominal values using the GDP deflator. All data is from the Federal Reserves with the sample period being from 1960:01 to 2007:04. On one hand, my choice to begin at 1960 is due to data availability and to end at 2007 is to avoid some possible structural changes in the private sector or policy maker’s behaviour due to the financial or euro crises. It is assumed that real GDP and real government spending are regarded as representative statistics for the real side and the nominal side of macroeconomics. In order to get stationary data, real variables are measured in logarithmic deviations from the linear trends. The inflation rate is obtained from the first difference in the log GDP deflator.
The Appalachian Regional Commission was created in 1965 as part of President Johnson’s war on poverty. Its identification of the counties under its purview was then, and has continued to be, much affected by the politics and geography of poverty. The Kennedy
administration established the Presidential Appalachian Regional Commission (PARC) in 1963, which consisted of federal officials and the governors of nine Appalachian states. 2 The PARC hired a staff of academics that produced a report identifying 340 Appalachian counties in ten states including Ohio (ARC, 1964). To aid passage of the Appalachian Regional Development Act of 1965, which created the ARC, Congress further expanded the list of Appalachian states to include South Carolina (Bradshaw, 1992). Mississippi and New York were added to the list in 1967, and more counties have been added since to bring the current total to 420 counties in 13 states. Adding counties to the ARC is a purely political process (Bradshaw, 1992), but its programs are designed to help poor counties, and poorer counties are therefore chosen for membership. For example, most Mississippi counties were added in 1967 explicitly because of their poverty. Though poor, most of these counties are not topographically, demographically, or culturally part of the Appalachian region. Similarly, many counties in topographically flat but economically depressed northeastern Ohio have been added to the ARC since that region’s economic decline began in the 1970s. Thus, the ARC’s county designations are clearly not exogenous to income growth rates, raising issues of bias and inconsistency in coefficient
This dissertation studies three questions related to the growth of China. In the rst essay, I primarily explore the multiplier of employment growth in the manufacturing sector. It provides a picture of the spillover eect on employment generated by the growth in the manufacturing sector. It is found that for every ten jobs created in manufacturing, 3.4 additional jobs will be generated in the non-tradable sector. The multiplier is also heterogeneous along skill intensity of manufactures, specic service industries, and geography. In the second essay, I investigate the impact of industry and services on economicgrowth at the local level in China. The essay answers the question that whether cities can take advantages of their early start in subsequent growth. The analysis also sheds light on the current debate that whether the industry is still important to economicgrowth and whether the service sector has become a primary driver of growth. I nd robust evidence that increase in the industry output share leads to a signicant increase in the growth rate of GDP per capita. Services, however, do not show a robust impact on growth. In the last essay, I provide a theoretical model to illustrate the temporary rural-urban migration in China. The model features the role of urban/rural service price dierential that generates the pattern of return migration.
explaining the growth process (see Römer 1994 for a survey on this issue). The pioneers attempted to incorporate long-run growth within the neoclassical structure by suspending one or more of the assumptions of the neoclassical model. For example Rebelo (1991) generates perpetual growth in his 'AK' model by assuming constant returns to scale to capital. Lucas (1988) does the same but by incorporating an externality from human capital accumulation which in turn generates increasing returns to scale in the three factors of production. Other approaches such as Grossman and Helpman (1991) attempt to model technology creation as due to active profit seeking activity. These models rely on the notion that innovation is accompanied by the creation of knowledge as a by-product which then adds to the existing stock of public knowledge. The increase in the stock of public knowledge in these models lowers the cost of future innovation, hence the externality from current innovation on future output. It is important to note that all the recent models of endogenous growth, including Römer (1986, 1990), Lucas (1988), Jones and Manuelli (1990), Rebelo (1991) and Grossman and Helpman (1991), modify the orthodox neoclassical model so as to admit long-run growth in per-capita income (see Hammond and Rodriguez-Clare 1993 for details of the relationship between the above models). These developments within endogenous growth theory have created a framework in which economic institutions and policies have long-run effects on growth rates.
predict that high transport costs produce inefficiently high specialization in agriculture, and that investments in road infrastructure would lead to significant reallocation of labor to the nonfarm economy. Khandker et al. (2009) use propensity score matching to evaluate the impact of a rural road program in Bangladesh, estimating that receiving a road lowers village poverty by 5-6% while increasing household consumption by 8-10%, although subsequent work suggests that some of these gains may not persist over time (Khandker and Koolwal, 2011). Most closely related to this paper, Banerjee et al. (2012b) study the impact of the PMGSY on a broad range of outcomes in a sample of 267 villages in Uttar Pradesh. They find that road construction results in greater access to government services, lower consumer prices, higher agricultural prices, increased employment outside of agriculture and less daily migration, with no effect on longer-term migration. While the majority of evidence points towards large economic gains from the construction of rural roads, some studies have suggested that low incomes and population densities in rural areas may not generate sufficient demand for transportation services on rural roads (Raballand et al., 2011).
statistical significance. In the analysis, since a dummy has been used to account for developed countries, GDP per capita is not used separately. The analysis also reveals that higher initial values of the urban proxy also lead to lesser growth in urbanization.
As regards to the other coefficients, the interaction term for the initial level of LLY and the developed country dummy as also the developed country dummy itself have a positive coefficient, as expected. This reiterates the scatter plots for developed nations that revealed that very high values of LLY are associated with higher urban growth in developed nations. Further, as expected, higher share of exports to GDP has a positive coefficient implying that higher trade openness lead to higher urbanization, higher level of communication infrastruc- ture have a negative coefficient (implying urban deconcentration) as does higher FDI inflows as a share of GDP. Higher contribution of the agricultural sector to GDP should mean a less industrialized economy and hence less urban. So we ideally expect a negative coefficient as is found for the proxies of urban population in relation to total population and urban gigantism. But for the H-F index of urban concentration and relative urban primacy the coefficient is positive. This can be explained that primarily agricultural economies typically have fewer big cities and hence as the economy develops, people and businesses typically flock into those cities.
However, the potential benefits of ICT and RTD investments need time to spill over the whole economy to significantly improve productivity statistics 15 . Increased
productivity derived from ICTs and technological change calls for new types of business organisation, education and professional training in order to spread new technical and economic opportunities. The experience of the USA and other countries reveals the importance of bringing flexibility and competitiveness to the markets in order to facilitate the diffusion and beneficial use of ICTs and reduce the time needed for their benefits to spill over the general productivity of the country. This transitional problem was aggravated in Spain by the boom that occurred after the introduction of the Euro (1999-2008), when low interest rates and widespread access to credit resulted in a housing bubble with extraordinary growth in the construction sector, and an overall rise in salaries that negatively affected the country’s productivity and competitiveness.
results for every specification. However, the sign of the coefficient associated with the lagged dependent variable is negative in the first period, but it becomes positive in the second period, meaning that a process of divergence was taking place (even though not significantly).
To have a clear vision, we reported a graph with four scatterplots associated with columns 1 and 4 of Table 3.6, and columns 1 and 3 of Table 3.7 (the regressions evaluating unconditional convergence). It is straightforward to observe the presence of unconditional convergence in population growth rates at province-level in the first period, culminating with the end of the Napoleonic wars and the Restoration (see figure 3.4). The least populated areas were catching up with the most populated ones to a significant extent. By contrast, during the “Risorgimento”, such a pattern is not visible, if not in a non-significant way. Looking at regional scatterplots the landscape is not different. All the Italian regions follow the dual regime with no exceptions. A convergence process is at stake in the low regime, whereas divergence in population occurred after 1821, mainly driven by the northwestern regions, which were likely to be at the beginning of a phase of divergence. It is even interesting to note that Piedmont and Emilia Romagna, two regions longer hit by Napoleonic wars, experienced among the lowest growth rates. Only Lombardy, another region at the center of war scenarios, had comparatively higher growth rates signaling a resurgence of agricultural and industrial activities ( Sella [ 2014 ]).
The paper has three main findings. First we provide evidence of heterogeneity across cultural traits in the speed with which they evolve across generations and con- verge to the prevailing norm. We document the persistence of family values (parental control on teenager’s access to contraception, ease of divorce, and frequency of social events with relatives, the role of women in society at large and in politics), political views, and deep individual religious values (as reflected in the answers to questions regarding belief in the frequency of prayer and approval of prayer in public schools). As a result, the values of immigrants of fourth-or-higher generation still bear strongly the imprint of their ancestors, who migrated to the United States many decades ear- lier. We also show that attitudes towards cooperation (the trustworthiness, helpful- ness and fairness of others), children’s independence, and sexuality converge, instead, more quickly, as successive generations adapt to the norms of the new society in which they live. The same is true – namely relative fast convergence – for the fre- quency of attendance to religious services. The latter reflects the social dimension of the religious experience and behaves differently from the other slow moving per-
wages, and …rm performance by analyzing data for 2000-2010. The major …nding is that the privatization is a major spur to increased e¢ ciency and pro…tability, and lead to a reduction in employment as well. This result is consistent with some previous studies while contradicts with others (see, e.g. Chen, et al., 2006), and contributes to the debate on whether and how privatization increases e¢ ciency and pro…tability in the sense that it is based on newly collected data for listed …rms in China. As I discuss later in the paper, there are good reasons to suspect that empirical …ndings relying on survey data for very limited industries and/or regions might be biased. The data used here have many advantages. First, the accounting and reporting systems of listed …rms are supervised and regulated by securities regulators, such as China Securities Regulatory Commission. Hence, the annual reports of listed …rms provide more accurate and reliable data about corporate governance, …nancial activities and …rm performance. Second, my data cover 226 listed …rms in over 100 cities (including counties) and 21 industries for 2000-2010. These …rms are located in the east, west and middle part of China. That is, my study is not limited to the developed cities or rural areas like many other papers are (see, e.g. Li and Rozelle, 2001). Also, a long-run study encompassing 11 years provides a great opportunity to examine both immediate and perennial e¤ects of privatization. Third, since Chinese listed …rms are consistently identi…ed by stock IDs (STKID), I am able to match …rm data from di¤erent sources and track a …rm as long as it is listed. This unique feature encourages further investigation of my study on privatization in China.
Shortly after a sluggish and mild recovery came the joint adhesion to the European Community in 1986. Lower oil prices along with the inflow of European structural funds, foreign direct investment, gradual privatization of state monopolies, deregulation of prices and markets fostered economic performance until the 1992 recession in Western Europe. On top of this widespread contraction, the Maastricht treaty imposed additional constraints on fiscal and monetary policy in order to transition to the euro currency a decade later. The criteria to adhere to the European Monetary Union included: “inflation over 12 months could not exceed by more than 1.5 percentage points the average rate among the three EC countries with the lowest inflation; long-term nominal interest rates over 12 months could not exceed by more than 2 percentage points the average for the same three countries; the currency had to remain in the narrow band of the exchange rate mechanism for at least two years without devaluation; the budget deficit should not exceed 3 percent of GDP; and total public debt could not exceed 60 percent of GDP” (Maxwell and Spiegel, 1994, p.51).
In Argentina, geographical conditions made this country exceptionally apt for the breeding of cattle and growing cereals, which constituted the main engines of its economy until 1920. The commercial exploitation of cattle started in the late second half of the XVIII century with the appearance of the saladeros, where salt-cured beef would be produced. Salt-cured beef was a rather unsophisticated product th at was mostly exported to Cuba and Brazil to feed the slaves there. In fact, the industry of the saladeros did not mean a big push to the Argentinean economy, which was at that time still a very marginal country within the world economy. The big boom for the cattle industry in Argentina actually came about much later with the introduction of the cold storage by the end of the XIX century. This technology perm itted selling chilled and frozen beef in Europe, attracting thus well-to-do consumers from th at continent.3 During this period, Argentina grew on average at rate of 5% yearly, attracted millions of immigrants from Europe and became one of the richest countries in the world.4 The exportation of chilled and frozen beef was undoubtedly one of the main activities th at spurred this phase of fast and steady economicgrowth in Argentina between 1880-1920.5
The final step was to bring the sectoral real GDP series up to the present period. This was done using several editions of the Canadian Economic Observer. The data on real GDP have been organised into a series for the aggregate economy and for the three main sectors of agriculture, industry and services. The data are also avail- able at a more disaggregated level but have been organised for ease of international comparisons. Agriculture includes arable, pastoral, forestry and fisheries; Industry includes mining, manufacturing and construction; Services acts as a residual in- cluding all remaining categories, and includes house rents. 8 The most contentious aspect of this aggregation is the inclusion of mining in the industrial category. The decision to proceed this way follows Broadberry and Irwin (2007) and makes for an easier comparison with existing long-run data that may be used in future studies. For many reasons, such as capital intensity and minimum efficient scale, mining is more akin to other secondary areas of production. When comparing Canada and Australia, the inclusion of mining as an industrial pursuit will result in Australia having a much larger share of output and employment in industry than if mining were included as a primary activity. Mining in Australia was a positive contributor to average labour productivity and will bias my results towards a more impressive secondary sector in Australia, strengthening my conclusions on Canadian manufac- turing.
The last ten years have seen numerous papers utilizing natural experiments to provide variation in income generally and natural resource wealth specifically, primarily at the country level, to understand the determinants of conflict. Miguel et al. (2004) use weather shocks to find that economicgrowth in Africa strongly reduces the likelihood of civil conflict. Bruckner and Ciccone (2010) find similar results using fluctuations in the prices of export commodities in sub-Saharan Africa, perhaps the closest existing paper to ours methodologically. Other papers find the opposite effect. Angrist and Kugler (2008) use within country variation in coca suitability to study the effect of a large increase in the demand for coca, finding an increase in conflict as groups fought over the rents in the coca trade. Still other studies find that resource wealth, once other variables are properly controlled for, has no impact on conflict or the overthrow of governments (Bazzi and Blattman, 2011). Cotet and Tsui (2013) use new oil discoveries to provide exogenous variation in resource wealth, also finding no significant effect on conflict. Dube and Vargas (2012) attempt to rationalize these disparate findings, arguing that resource production may increase conflict over government revenues but also decrease conflict through increasing the opportunity cost of time. They find evidence for this by comparing the differential effects of oil and coffee price shocks in Colombia; positive shocks to oil, a capital-intensive commodity, result in increases in conflict, while positive shocks to coffee, a labor intensive commodity, have the opposite effect.
The current analysis cannot provide direct evidence on taxation by rebel groups, which is the key mechanism within my framework that explains the differential im- pact of rainfall shocks in mining regions. The Maoists publicly campaign against mining activity on the grounds that mines lead to pollution and the displacement of the tribal population. Rebel groups in mining regions are thought to bank on the wide-spread resentment against mining activity (Kujur, 2009), although certain authors emphasise that only small number of communities were directly affected by displacement (Kennedy and King, 2009). The first order effect of grie- vances against mines should operate through average levels of violence, which are accounted for by the fixed effects. However, the adverse impact of mining activity on rural communities could suggest alternative explanations of the observed dif- ferential impact of rainfall in mining regions. In particular, rebel groups could be more effective in recruiting from mining regions because of two reasons. First, it may be that a given rainfall shock has a larger impact on agricultural producti- vity of potential recruits as a result of environmental degradation or displacement. This channel could even be strengthened through political economy factors. If districts that produce minerals have weaker political institutions, this could exa- cerbate the impact of a given rainfall shock (as suggested in the ordered conflict model of Besley and Persson, 2010). While the analysis cannot fully rule out this possibility, the estimated rice production function in Table 1.2 and Table 1.4 failed to pick up any differential effect of rain on agricultural output in mining regions. Furthermore, a political resource curse interpretation is undermined by the fact that policies are set at the state level and all selected states (with the exception of Bihar) produce key minerals. 60 A second channel that relies on the environmental
In this paper, we build a two-country and two-sector endogenous growth model where clean and dirty technologies innovate to compete for global market leadership in final good production. Our framework builds on the micro-founded directed technology change model developed in Acemoglu et al. (2016a), which allows for a comprehensive quantitative eval- uation. In both countries, the final good combines components produced using clean or dirty intermediates goods. The intermediate goods may be sourced from foreign or domestic producers. For each intermediate good, a home and a foreign firm compete for global mar- ket shares, and they improve the quality of their product through international knowledge spillover. The entrepreneurs in each country invest in R&D to enter the market. Meanwhile, clean and dirty sector are competing for market share in final good production with the dynamic evolution of technology. In addition to each country’s choice of research subsidy and carbon tax levels, international trade opens up a new policy dimension in the form of tariffs on dirty goods. We parameterize the model to match key trade, innovation, climate and growth facts, with a specific focus on the US and China. Using standardized firm-level data on research and patenting in both the US and China, we quantify the incentives for both clean and dirty innovation faced by firms.
BSC emphasizes that financial and nonfinancial measures must be part of the information system made available to employees at all levels of the organization. BSC translates a business unit‘s mission and strategy into tangible objectives and measures. The measures represent a balance between external measures for shareholders and customers and internal measures of critical business processers, innovation, and learning and growth. The measures are balanced between the outcome measures—the results from past efforts—and the measures that drive future performance. The scorecard is balanced between objective, easily quantified outcome measures and subjective, somewhat judgmental, performance drivers of the outcome measures. The Balanced Scorecard is more than a tactical or an operational measurement system. It is a strategic management system used by companies with a long-term focus to manage their strategy (Kaplan & Norton, 1996).