rafmacalaba/datause-encoder-data huggingface dataset:
46 commute to regions of low unemployment and relatively high wages. In the CR labour mobility goes into the direction which is predicted by theory.

# 3.3.4 The Czech labour market: outflow out of the labour force

Workers may leave the labour force either directly from employment or after a period of unemployment. In the CR immediately after the beginning of the reform policies large numbers of pensioners and women left the labour force. Czech women at any rate have the left the labour force in larger numbers than in other transition economies where women have preferred to remain in the state of unemployment (cf. IMF, op. cit and Ham et al., op. cit.). This labour force withdrawal of large numbers of pensioners and women has certainly in the short run softened the unemployment problem in the CR. What is, however, more interesting is the temporary labour force exit of generally young and relatively well skilled persons who have chosen to work in Germany and Austria.<sup>39</sup> These persons might relieve pressure on the Czech labour market in the medium run since, if they chose to work at home, they might very likely "crowd out" of employment persons who are now at work but have "worse characteristics" than the temporary "emigrants".

According to informal estimates of German and Czechs officials Germany there is about one illegal Czech worker per legal Czech worker and there are altogether about 100.000 Czech who work abroad. In 1993 there were about 34 thousand Legally employed Czechs in Germany, of whom 70% worked in Bavaria and 40% in the Bavarian Border Regions (cf. table 14). What should be looked at is the development after 1990 as Czech workers in 1990 were mainly emigrees who had worked in Germany for a long time. The dynamics for the years 1991-1993, while impressive, are not that substantial to have caused a major reduction in the Czech unemployment rate. The 40% working in Bavarian Border regions are mainly persons residing close to the border who are allowed to work there permanently as long as the local Bavarian labour market situation makes this possible. With the onset of the recession in Germany in 1993 new hirings of such cross border commuters declined somewhat as table 14 shows. While the numbers of cross border commuters is not large relative to the Czech labour force one should note, though, that the CR is the only transition economy bordering at a Western country and having secured such a generous agreement on in principal limitless crossborder commuting. The impulse the commuters give to the local economy on the Czech 39 Svejnar, Terrell and Munich (1995) provide some evidence of significantly lower inflows into unemployment in border regions.
# **Appendix Table I. 11: Unorganized Sector Log (Employment) and Spillovers from Small, Medium-sized, and Large Organized Plants**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||Small Organ|ized Plants|Mediu|m-sized|Large Orga|ized Plants|
|||<br>_Other-s_|_ector Emplo_|<br>_yment Spillo_|<br>_vers_||
|Horizontal Employment Spillovers|||||||
|from Organized Sector|0.2766***|0.1315***|0.1349***|0.0307|0.1353***|0.0558**|
||(0.0390)|(0.0347)|(0.0338)|(0.0282)|(0.0301)|(0.0257)|
|Forward Employment Spillovers|||||||
|from Organized Sector|0.1865|-2.4068***|0.6144**|3.1810***|0.0422|-0.1135|
||(0.2799)|(0.9256)|(0.2478)|(0.5240)|(0.2707)|(0.5850)|
|Backward Employment Spillovers|||||||
|from Organized Sector|3.7769***|1.7919**|1.8564***|1.1810***|0.8154***|0.4686+|
||(0.3652)|(0.8805)|(0.2231)|(0.3847)|(0.1359)|(0.3231)|
|||_Other-s_|_ector Produ_|_ctivity Spillo_|_vers_||
|Average TFP of Horizontal-linked|||||||
|Organized Plants|0.0177|0.0583|-0.2350|0.0048|-0.2827++|-0.0514|
||(0.1226)|(0.1116)|(0.2109)|(0.1815)|(0.2177)|(0.1952)|
|Average TFP of Forward-linked|||||||
|Organized Plants|0.1316++|1.4909***|0.0552|1.2862***|0.4307***|-0.8627**|
||(0.1005)|(0.3949)|(0.1428)|(0.1675)|(0.1368)|(0.3720)|
|Average TFP of Backward-linked|||||||
|Organized Plants|-0.0955|-1.0399***|1.2728***|5.7880***|0.9936***|-0.0168|
||(0.0750)|(0.2836)|(0.2062)|(0.5210)|(0.1668)|(0.4664)|
|||_Own-s_|_ector Emplo_|_yment Spillo_|_vers_||
|Forward Employment Spillovers|||||||
|from Unorganized Sector|0.4671+|4.3433***|0.2256|-6.1909***|0.0700|-1.2611+|
||(0.3042)|(0.7311)|(0.3335)|(0.8849)|(0.3486)|(0.8698)|
|Backward Employment Spillovers|||||||
|from Unorganized Sector|0.6097***|1.4194***|0.7627***|2.8699***|0.9405***|1.4336***|
||(0.1537)|(0.4551)|(0.1508)|(0.8558)|(0.1631)|(0.4425)|
|Constant|-45.0019***|-57.7580***|-|-14.6686++|-19.9992***|1.1868|
||(5.0184)|(10.9365)|(4.8031)|(10.2193)|(5.7759)|(10.9272)|
|Observations|5888|5888|5888|5888|5888|5888|
|R-squared|0.1354|0.3506|0.0952|0.3459|0.0784|0.3472|

_Note: The independent variables are constructed using the total employment by large organized plants in a stateindustry cell. Small plants are defined as those with less than 50 employees, medium-sized plants have 51-150 employees and large plants are defined as those with more than 151 employees. All specifications contain panel (state-industry) fixed effects as well as year fixed effects. Columns 2, 4 and 6 contains state-year and industry-year fixed effects. Standard errors are clustered by the state-industry level. Significance at the 20% level is indicated by ++, at the 15% level by +, at the 10% level by *, at the 5% level by ** and at the 1% level by ***._ 64
China” in third markets as well as in their own backyards. In 1993 China’s exports of machinery to the world were almost the same as Malaysia’s, however, in 2004 China’s machinery exports were already 4 times more than Malaysia’s. As for home markets, manufacturers of motorcycles in Indonesia have complained about the flood of cheaper Chinese versions. Another concern is the loss of FDI resulting from positive externalities from manufacturing machinery products in China rather than in the other Southeast Asian countries. Firms in Japan, South Korea, and Taiwan, China might be leaning towards relocating to China instead of producing in Indonesia, Malaysia, Philippines, or Thailand, which could mean loss of jobs and investment in these countries.

Despite China’s bold maneuver, the big dragon shaking its tail could also benefit the little ones. China’s increasing role as an assembly hub could provide opportunities for suppliers of components from Southeast Asia. The current pattern of trade and investment suggests that machinery is put together with the help of a network of suppliers known as a production network. As a result of the fragmentation of the production process, a Chinese assembler needs only to focus on its competitiveness in assembling parts and components while relying on highly skilled suppliers in Southeast Asia or elsewhere with lower cost.<sup>3</sup> Chinese assemblers can also delegate the manufacturing process of components that mainly use resource-based inputs - such as rubber and metallic ores - to resource rich countries such as Indonesia and Malaysia.

Thus what might be interesting for many, including policy makers in Southeast Asia, is the extent of externalities resulting from China’s increasing machinery exports. Against this background, we explore how trade in components and finished products of machinery is behind the trade between Southeast Asia and China. Second, we look at the competitiveness and relative sophistication of China’s machinery products versus those made by Southeast Asian countries. Third, we use regression analysis to look at whether expansion in Chinese machinery exports has any impact on unit value and export composition in machinery from

> 3 Jones and Kierzkowski (2001) provide a general framework on the fragmentation of production activities. Ando and Kimura (2007) argue that falling costs of servicing different production blocks have driven the fragmentation process of trade in machinery towards economies in Developing East Asia.

> <sup>3</sup>
<!-- Start of picture text --> Reviewed in the study 133 100% 734 100% 1,297 100%<br>With each type of disability question:<br>- Washington Group Short Set (WGSS) 32 24% 4A 6% 61 5%<br>- Other functional difficulty questions 46 35% 67 9% 90 TM%<br>- Activity of Daily Living (ADL) questions 15 11% 24 3% 36 3%<br>- Broad activity limitation questions 36 27% 53 7TM% 71 5%<br>- General disability questions 50 38% 81 11% 113 9%<br>- Other disability questions 43 32% 54 7% 75 6%<br>With any disability question 100 75% 231 31% 350 271%<br>With functional difficulty questions (WGSS and/or other) 66 50% 111 15% 156 12%<br><!-- End of picture text -->

|Reviewedinthe study|133|100%|734|100%|1,297|100%|
|---|---|---|---|---|---|---|
|Witheachtypeofdisability question:<br>|||||||
|-WashingtonGroupShort Set(WGSS)|32|24%|4A|6%|61|5%|
|- Otherfunctional difficulty questions<br>|46<br>|35%<br>|67<br>|9%<br>|90<br>|TM%<br>|
|-Activity ofDailyLiving(ADL)questions|15|11%|24|3%|36|3%|
|-Broadactivitylimitationquestions|36|27%|53|7TM%|71|5%|
|- General disabilityquestions|50|38%|81|11%|113|9%|
|- Other disability questions<br>|43<br>|32%<br>|54<br>|7%<br>|75<br>|6%<br>|
|Withanydisabilityquestion|100|75%|231|31%|350|271%|
|Withfunctionaldifficultyquestions(WGSSand/orother)|66|50%|111|15%|156|12%|
reduce their budgetary expenses through spinning off their public infrastructure operations. On top of that, in many developing countries the public sector is among the largest employers in the economy. If this is the case, the authorities, mainly politicians, are likely to be sensitive to a possible reduction in employment after the contracts.

A stylized fact about general private participation in infrastructure may be that the network size (such as connections) tends to be enhanced and the unit operating cost would likely decline. Private management also increases labor productivity (such as delivered services per employee). This improvement typically stems from retrenchment in excess employees. The quality of services would also improve. Tariffs may or may not increase.<sup>5</sup> Gassner _et al_ . (2007) also shows that the improved performance of electricity (and water) utilities involving private sector participation is largely associated with an increase in labor productivity. In railways, the Estonian divestiture experience where a national railway company was vertically unbundled and privatized indicates that labor strength has reduced by 37 percent and labor productivity increased dramatically. It became four times as high as that of the EU countries (World Bank, 2006).

As far as transport concessions are concerned, this employment effect may be a crucial issue to implement PPP transactions successfully. State-owned railway companies usually absorb a large number of employees. Under these conditions, the number of firms participating in the bidding process is expected to be small. Then, the governments would become even more cautious about other project aspects than prices. In our sample, about 32 percent of railway sector concessions relied on multidimensional auctions, possibly to accomplish more than one policy objectives simultaneously.

As per Estache _et al_ . (2002), in the Argentine railway freight concessions during the 1990s, the winning bid was selected based on the weighted score of future investment, staff accession and service quality. It is pointed out that the inclusion of the staff transfer criterion was clearly a political compromise. In the U.K. experience, Nash and Smith (2007) indicate a similar concern; wage increases in the passenger rail sector after the private sector involvement were in sharp contrast to the bus industry where wages sharply fell.

> 5 For instance, the benchmarking data for the electricity distribution sector in LAC 1995-2005, <u>http://info.worldbank.org/etools/lacelectricity/home.htm</u>

12
Following Quah (1993), it is assumed that the income of each municipality follows a first-order Markov Process with time-invariant transition probabilities. This is, a municipality’s income of tomorrow depends only on its income of today. In this way, let Ft denotes the distribution of incomes across municipalities at time t and the law motion can define its evolution: Ft+1 = MFt Where M maps one distribution into another and encodes information on whether poor (rich) economies transit from t time to t+1 to widely different income levels.

In the discrete version of this approach, we can take each of Rio Grande do Norte’s municipality per-capita income relative to the State average and divide municipalities into income groups. Quah (1993) suggests dividing the observed data into approximately equally sized categories. We divide the data in five groups: poor (P), low (L), medium (M), upper (U) and rich (R) municipalities.<sup>8</sup> Consequently, M is described by a 5 x 5 Markov Chain Transition matrix, whose (j, k) entry is the probability that a municipality in state j in time t transits to state k in time t + s. The main diagonal of this matrix denotes persistence, as it represents the probability for a municipality remaining in its original group.

We estimate the transition matrix using per-capita income data for 150 of Rio Grande do Norte’s municipalities from 1970 to 1996. It is important to observe that the range for groups was calculated in each moment of time, as it is necessary to analyze the relative position of each municipality over time to avoid biases, since all municipalities show absolute per-capita income growth over time, but not necessarily a change in their relative position.

Quah (1993) built the one-step annual transition matrix, estimated by averaging the observed one-year transitions over every year, and one 23-year transition with data of initial and final time of his sample. However, the literature suggests that the choice of time interval may affect the probabilities, in other words, the transition matrix is very sensitive to time lag. According to Kremer _et al_ . (2001), transition periods longer than one year reduce the impact on the estimated transition matrix of high fluctuations in income and, consequently, the results are more robust. On the other hand, the longer the transition period is, the higher the mobility among classes. Hence, we construct a matrix with a 26-year transition, the maximum that our data allow.

> 8 Poor  (P)= 0 - (μ - 0.45*σ ); Low  (L)= (μ - 0.45*σ )  -  (μ - 0.30*σ );  Medium  (M)= (μ - 0.30*σ )  -  (μ - 0.10*σ ), Upper  (U)= (μ - 0.10*σ )  - (μ + 0.20*σ) and Rich  (R)=  > (μ + 0.20*σ ) where: μ  is the percapita income mean in the year i and σ is the standard error of per-capita income in the year i.

17
experience tend to prefer men. Foreign-owned firms, and firms hiring for certain customercontact occupations tend to prefer women.

Status and “suitability” for a job can often be gleaned from an applicant’s residence, as neighborhoods are often (unreliable) proxies for social class and implicitly, for human capital endowments. While clustering confers benefits of solidarity and networks for minorities, an address can also be an identifier and a stigmatizer. Clark and Drinkwater (2000) show that an individual’s probability of being observed in a particular labor market state depends on the ethnic composition of the neighborhood in which s/he lives. In a study of England and Wales, they found that ethnic minorities who live in enclaves have a higher likelihood of being unemployed and a lower probability of self-employment than compatible individuals who live in less concentrated areas. They acknowledge that while individuals can sort non-randomly, the potential benefits of living with co-ethnics are trumped by the deprived nature of the urban areas in which minorities tend to cluster.

Like neighborhoods, language, speech patterns, accents and non-verbal cues (such as a particular sound or a head bob) can also be identifiers – they give salient clues about an individual’s social status and family background. It is perfectly acceptable to ask for language skills as part of eligibility criteria but when spoken language identifies the social status of an applicant and has no bearing on the needs of a job, but influences hiring decisions, it is an enabler of discrimination. Once such an applicant is hired, the lack of a sophisticated spoken language or existence of non-verbal cues like physical mannerisms, can lead to discriminatory behavior in the workplace in much the same way as it does in educational institutions. This in turn could affect earnings and/or promotion. That foreign accents or those that reflect stereotypes about a worker’s social status affect hiring decisions is known anecdotally, but this is also borne out in some of the empirical literature. Bendick et al (2009) in a controlled experiment in New York found that the way applicants spoke English mattered significantly in the likelihood of being hired (but that race mattered over and above English proficiency). White applicants with slight European accents were 23.1 percent more likely to be hired than white testers with no accent. However, accents in nonwhite applicants made no difference.

18
# savings.<sup>50</sup>

These associated reforms are crucial to sustain the “burden reduction” objective of the RFR reform **.** As illustrated by the numbers in Table 22 above, subsidies from higher-level governments replaced about 35 percent of the pre-RFR revenues in 2002, accounting for two-thirds of the reduction in farmers’ burdens. To prevent the burden from “rebounding” or negatively affecting public expenditures, additional sources of savings would have to be found. One such source is improved efficiency due to farmers’ participation in project selection. For the first time, the RFR presents the public with the possibility of choice – farmers can vote (with a two-thirds majority) to “tax” themselves to undertake infrastructural investments _(yishi_ _yiyi)_ . This new arrangement will presumably weed out unwanted projects and ensure a more responsive pattern of investment. Another potential source of savings is from cutting rural administration and raising efficiency in service provision. The reform design of the RFR explicitly relies on these efficiency gains to alleviate burdens also by encouraging farmers’ involvement in the delivery of goods and services.

# **5.3.  Agricultural Tax Abolition (ATA)**

The RFR was quickly followed by the abolition of agricultural taxes **.** In 2003 the government announced that beginning in 2004 provinces should try to reduce the agricultural tax rates (just raised to 7 percent under the RFR) by 1-3 percent per year, to reach a zero rate by 2007. This reform was further accelerated, with the government announcing in December 2005 that the tax had already been abolished in all but three provinces.<sup>51</sup> By early 2006, it had been completely abolished nationwide.<sup>52</sup> Building on this momentum, in February 2006 the agricultural special products tax and the slaughter tax were also formally abolished.<sup>53</sup> The ATA was a response to the growing complaints that the agricultural taxes were unfair **.**

> 50 _China Daily_ , November 17, 2004.

> 51 These were Hebei, Shandong, and Yunnan.  Even in these provinces, the tax had been abolished in more than 210 counties.  Jin Renqing interview in _People’s Dai_ ly, December 31, 2005.

> 52 The Decision of the Standing Committee of the National People’s Congress on Abolishing the Regulation of the People’s Republic of China on the Agriculture Tax, issued December 29, 2005, formally abolished the agricultural tax effective January 1, 2006.

> 53 Decision of State Council Order No. 459, issued on February 17, 2006, for immediate implementation.

49
The low employment-to-population<sup>ratio in Croatiais,inter alia,the resultof a</sup> mode of labor market<sup>adjustmenttonumeroussupplyanddemand"shocks"</sup> associated with the economic<sup>transition. Asinmostothercountriesof Centraland</sup> Easter Europe (CEE),<sup>thebruntofadjustment hasbeen born byemployment rather</sup> than wages. Employment has declined<sup>while-</sup> once the growth of output<sup>has</sup> resumed -- wages have<sup>roughly followedproductivityincreases.</sup> Since 1995 employment has declined<sup>byafewpercent,while realwageshavegrownby about</sup> one third and productivity<sup>(in industry)has increasedeven more (Table3).2</sup>

**Table 3 Selected indicators**<sup>**of labor market dynamics,1995-2001**</sup>

||**1996**|**1997**|**1998**|**1999**|**2000**|**2001**|
|---|---|---|---|---|---|---|
||||_1995= 10_<br>|_0_<br>|1330|1318|
|Realgrosswages<br>|107.9<br>|117.2<br>|124.9<br>|132.1<br>4|.<br>943|.<br>963|
|Employment<br>|103.7<br>|96.1<br>|99.1<br>|97.<br>|.<br>|.<br>1608|
|Laborproductivity(industry)<br>|111.3|124.5|135.4|140.7|146.7|.|
|Memorandum:<br>||||13551|1605|158|
|LFSunemploymentrate,<sup>%</sup>|10.0|9.9|11.4|.|.|.|

# I indicates the break in<sup>time-series</sup>

Note: In 2000 the sample<sup>frame for theLaborForceSurvey(LFS)was changed andaccordingly,</sup> the results are 'not fully<sup>comparableover time.</sup> Source: Central Bureau<sup>of Statistics, the WorldBank database, Author'scalculations.</sup> The fall in employment<sup>coupledwithsignificantproductivitygains reflects</sup> what can be called a "productivity<sup>catch-up".Overmanningwascommoninsocially</sup> owned firms in Croatia,<sup>whichwasassociatedwithlowlaborproductivity.</sup> As the transition progressed<sup>enterprises havebeensubjecttoanintensifiedcompetitive</sup> pressure, coming from<sup>thedeveloping private sector aswellasfromforeign</sup> competitors, increasingly<sup>enteringthe Croatianmarket.</sup> This has forced firms to reduce costs, cut employment<sup>and improve productivity.For manyfirms,especially</sup> the privatized ones, downsizing<sup>hasbecomeaprerequisite forasurvivalinamore</sup> competitive environment.<sup>Toillustratethisprocess,anaveragefirmsizehasalmost</sup> halved during the transition<sup>in Croatia,decreasingfrom over22 employeesin1993to</sup> about 12 employees in<sup>2000.3</sup>

> 2 Data on employment levels<sup>can be inaccuratedue to problemswithadequate coverageof</sup> small private firms by the<sup>employmentsurvey.</sup> 3 Data refer to registered firms<sup>whichare legal persons (FINA/ZAPregister).</sup>

_-5-_