dataesr/scientific-paragraphs-categorization huggingface dataset:
We then matched the list of politically connected businessmen to firms listed on the Cairo stock exchange. The Orbis database includes this information on the board members, managing directors, or major shareholders of 854 firms that are currently or were formerly traded on the exchange. 5 The names of 32 businessmen identified in step one matched unambiguously the names of board members, managers, or major shareholders of 104 firms. Since these 104 firms could be holding companies or investment funds, we further used the Internet to identify the names of all subsidiaries (up to two tiers) and then matched these subsidiaries with firms in the Orbis database. This process identified 469 firms that are unambiguously controlled, directly or indirectly, by a connected businessman. Of these firms, 47 have a politically connected businessman as a general manager (CEO), 140 have at least one connected board member, and in 334, at least one connected businessman or firm was unambiguously identified to have an ownership stake.
Of course, it also matters how "close" the political connection to the businessman is, however, we do not have information to distinguish between different types of connections as all connected businessman are considered to have first tier political influence over regulations and their implementation. Having identified politically connected firms, we linked these to data on firm performance in order to compare their performance with that of unconnected firms within their sector. These data were taken from the Orbis database. It contains employment data for 20,000 establishments between 2003 and 2012; operating revenues for about 700 large establishments; and profits for about 400 large establishments. To analyze the impact of political connections on aggregate employment growth, we take advantage of establishment census data from the department of statistics in Egypt (CAPMAS).
We match these data to our data on the sectoral intensity of cronyism to see if 4-digit sectors with more politically connected firms benefit from more NTMs and are more energy-intensive (receive more energy subsidies). Moreover, we test whether connected firms benefit from other types of regulatory capture. We do not know the specific regulatory experiences of connected firms relative to unconnected firms, but through World Bank Enterprise Survey (WBES) data, we can compare the regulatory environment across 4-digit sectors with more and fewer connected firms. We pool all available surveys for Egypt between 2004 and 2008 in order to maximize the representativeness of the perceived policy data at the sector level. Overall, the WBES data identify the regulatory environment perceived by more than 4,200 firms that were active in 90 (ISIC Rev.
In the second part of the paper, however, the data allow us to make stronger causal inferences. Many sectors exhibited no politically connected firms in 1996 (i. e. , 145 4-digit sectors non-agriculture sectors). Between 1996 and 2006, however, politically connected firms entered into some of these sectors, but not others. We estimate the impact of political connections on aggregate sector growth by comparing previously unconnected sectors that experienced entry by connected firms with those that did not experience entry. Our identifying assumption is that crony firms did not enter new sectors with an (unobservable) lower growth potential. 11 Such an unobservable correlation would lead to a bias in favor of our results (lower employment growth after the entry of crony firms into new, previously unconnected sectors).
We present several pieces of evidence, however, that indicate that this scenario is unlikely including comparisons of the same sectors in other countries, showing no evidence that growth rates were lower in sectors where we observe crony entry in Egypt. Many of our results below are based on differences between sectors with and without politically connected firms. This gives rise to the concern that the results hinge on a small number of sectors that happen to have politically connected firms. In fact, of the 320 sectors in our database about half (49%) include connected firms (186 out of 372); 49 have at least one (33 sectors) and as many as 10 (one sector) firms with politically connected CEOs; 142 have at least one (57 sectors) and as many as 35 (one sector) firms with politically connected owners; and 165 have at least one (57) and as many as 35 (four sectors) firms with any form of political connection.
Firm performance, connected versus unconnected firms If politically connected firms have policy advantages over unconnected firms, they should be able to accumulate larger market shares and scale than would otherwise be the case. Employment and revenues should therefore be greater. The Orbis data has employment data for around 20,000 establishments. On average, the 436 connected firms in this dataset (33 connected firms have no employment data) have 941 employees compared to 253 employees among the remaining establishments. Orbis consolidated revenue data, available for 678 firms, reveals that 67 connected firms with data had revenues of $172 million, on average, four times higher than the 611 unconnected firms between 2003 and 2010. In addition, protected from entry, the profits and profitability (profits/assets) of connected firms should be larger.
The advantages of politically connected firms make them more profitable relative to other firms operating in the same sector. Thus, the performance differences are not specific to the (broader) sectors in which connected firms operate. Source: Orbis establishment database. Note: The establishment data are pooled across years (2003-2011). The first column reports the coefficient and t-statistic on the politically connected dummy variable from an OLS regression of the performance variable (e. g. , ln(employment)) on the dummy variable, which is equal to 1 for politically connected establishments and 0 otherwise. In the second (third) column, we control for 2(4)-digit sector dummies. *, ** indicates that the coefficients are significant at the 5%, 10% level. While we do not conduct a formal event study, we can still ask whether the profit advantage of connected firms vary with the strength of the Mubarak regime.
Political connections and non-tariff trade barriers Although tariffs fell in Egypt at the end of the 1990s, the use of non-tariff technical import barriers increased. 17 Building on data from a new World Bank database (WITS) measuring NTMs (Malouche et al. , 2013), Figure  2  illustrates the decline in average weighted tariffs from about 16. 5 percent in 1995 to 8. 7 percent in 2009 -but also a steady and offsetting increase in NTMs. NTMs primarily included barriers to imports such as exclusive licenses requirements, rules of origin, or quality year in which it is has been substantially revised. Unfortunately, the database does not distinguish between the two. controls (which leave scope for discretion) for imported products. As a result, Egypt had one of the highest NTM frequencies in the world in 2010 (Malouche et al.
In addition, the politically connected are likely to have a large advantage in securing private credit, if they enjoy implicit government guarantees. As usual, we classify WBES firms according to their 4-digit industrial classification and aggregate firm reports of access to land, credit or location in an industrial park at the 4-digit sector level. Then, as in the analysis of NTMs and energy subsidies, we ask whether sectors with more politically connected firms have better access. The WBES data include data from 3,040 firms in 91 4-digit (ISIC Rev. 3. 1) manufacturing sectors. 29 Out of 3,036 manufacturing firms, 1,431 reported acquiring land: 933 obtained the land from the government, 57 obtained it for free. In addition, 1,060 manufacturing firms are located in an industrial zone and 453 (out of 3,040) manufacturing firms reported a loan.
Do connected firms disproportionately benefit from the enforcement of rules? Politically connected firms also used their connections to reduce their own regulatory burden and the threat of predatory behavior by government officials relative to the burden and threats faced by their competitors. To see this, we again employ the WBES data, which contains firms' assessments of the burden imposed by various government policies and regulations. The WBES also asks firms for objective information, such as the time it takes to get a construction permit. Again, we supplement the WBES data with our information on the number of political connected per 4-digit manufacturing industries. Following Hallward-Driemeier et al. (2010), we also examine within-industry variations of firm reports of the regulatory environment.
is a matrix of firm level control variables, and T is a matrix of year dummies. The analysis is based on Orbis firm survey data; this is the only database that allows us to identify individual connected firms. Profit and revenue data are available for 250 larger manufacturing and mining firms of which approximately 50 are politically connected by any type; our analysis is therefore focused on these 250 firms. 37 37 We cannot include firm size as an additional control variable since the sample of firms that report profit data is small and many of these firms do not report their (consolidated) number of employees in Orbis. Thus, we only observe employment and profits jointly for eleven politically connected manufacturing firms and 40 firms overall. The sample includes all firms from the Orbis data with available information for the corresponding variables.
We then present data that supports our key identifying assumption that crony firms did not enter new sectors with an (unobservable) lower growth potential. 41 Finally, we document a key mechanism, consistent with the theory, through which crony entry might have suppressed employment growth. The estimation specifically tests whether employment growth declined over the ten year period between 1996 and 2006 in sectors that were initially unconnected (or open), but that experienced entry by crony firms. We use the following difference-in-difference estimation specification, whereby ∆  measures employment growth of the 4-digit sector s between 1996 and 2006,  indicates the entry of politically connected firms between 1997 and 2007,  are sectors without crony firms before 1997, X is a matrix of control variables (employment and age), and S a matrix of sector dummies: ∆ ,2006-1996 We do not expect to observe adverse effects when connected firms enter into sectors that were already dominated by connected firms.
193 0. 194 0. 194 0. 187 0. 189 0. 191 0. 070 0. 071 0. 070 Source: World Bank Enterprise Survey (WBES) data for Egypt 2004-2008 and sample of politically connected firms. Note: Number of politically connected firms is the number, in our database, in each 4-digit sector. The three different types of connections (ordered here by their restrictiveness) are defined in Table1. The number of employees (size) and firm age vary at the firm level. All regressions include 2-digit sector dummies. Standard errors are clustered at the sector level. *, ** indicates significance at the 10%, 5% level, t-statistics are reported in parentheses.
By the time the Keck observatory observed Saturn in February 2004 (a planetocentric solar longitude of L s = 287 • ), 16 months after southern summer solstice (October 2002), the warm South Polar Stratospheric Vortex (SPSV) was already well established poleward of 70 • S 4. Half a Saturnian year earlier, when the NASA Infrared Telescope Facility observed Saturn's North Pole in March 1989 (L s = 104. 5 • ), 15 months after the northern summer solstice (December 1987), the warm North Polar Stratospheric Vortex (NPSV) could already be seen 11. The longevity of Cassini's exploration of Saturn (2004-2017) now provides the first complete dataset to trace the growth of the NPSV, as Saturn reached northern summer solstice (L s = 90 • ) in May 2017. Previous work used 7-16 µm infrared spectroscopy obtained by the Cassini spacecraft 12 to trace the dissipation of the SPSV from northern winter (July 2004, L s = 293 • ) to northern spring (June 2014, L s = 56 • ).
An attempt to provide a spatially-resolved temperature retrieval of the stratospheric hexagon was unsuccessful, as the binned spectra did not have sufficient signal-to-noise to constrain the hexagonal shape of the temperature field as a function of altitude. We therefore cannot tell whether the hexagon is present at 5 mbar or at 0. 5 mbar, or a combination of both. However, data presented in the next section indicates that Saturn's banded structure is clearer at 5 mbar than at lower pressures, raising the likelihood that the hexagon is only detectable in the lower stratosphere (p > 1 mbar). Furthermore, the low signal in the pre-2014 data means that we cannot distinguish between scenarios where the hexagon is always present in the stratosphere irrespective of season, or the hexagon is allowed to extend upwards due to the seasonally-changing temperatures as summer solstice approaches (to be discussed below).
A wavenumber-6 feature is clear in each dataset near 78 • N (vertical red dashed line), although the 2014 stratospheric hexagon is rather noisy (Fig. 1b ). Using the sinusoidal fits, we detect a westward shift in the tropospheric hexagon vertices of 8. 5 ± 1. 1 • over 963 days (the uncertainty comes from the quality of the sinusoidal fit). Offsets between the tropospheric and stratospheric vertices were < 4 • in February 2017. peratures (panels j-l) at three different pressure levels (0. 5, 1. 0 and 5. 0 mbar). These were derived from averages of low-resolution CIRS spectra on a monthly temporal grid, and interpolated using tensioned splines  41  to reconstruct a smoothed temperature field. Horizontal dashed lines signify the peak of eastward zonal jets in the troposphere  9. The data are displayed as a function of time (years), but a second horizontal axis provides the planetocentric solar longitude (L s ) in degrees.
Methods Low-resolution CIRS time series. To track the evolving stratospheric temperature gradients as a function of latitude and time, we adopt a similar technique to previous work  12, 39  , truncating all CIRS interferograms so that they are all treated at the lowest possible spectral resolution of 15 cm -1. This means that all CIRS Saturn observations, including those that rode along with other Cassini instruments, are considered. These are binned onto a monthly time grid on a 2 • latitude grid (with a 1 • step size) for all latitudes, retaining only observations within ±10 • emission angle of the mean for each bin, and ensuring that this emission angle was smaller than 60 •. Data were also filtered for smearing due to fast motion of the focal plane across the disc; (known interferences; in-stances of negative radiances introduced by shifting instrument temperatures; and examples where fewer than ten spectra were available at a particular latitude and time.
These values were broadly representative of those extracted from the photochemical model  19. The retrieved profiles, based on this grid of priors, are shown in Fig. 6  for both the NPSV (L s = 88 • ) and the SPSV (L s = 346 • ). Some inversions fit the CIRS spectra better than others, but where multiple profiles overlap, we can be confident that it is the data (rather than the prior) that is driving the inversion. For example, temperatures only begin to diverge for p < 1 mbar, whereas and south polar temperatures (panels j-l) at three different pressure levels (110, 220 and 330 mbar). These were derived from averages of low-resolution CIRS spectra on a monthly temporal grid, and interpolated using tensioned splines  41  to reconstruct a smoothed temperature field. Horizontal dashed lines signify the peak of eastward zonal jets in the troposphere  9.
Acknowledgements This work is based on data acquired by the  Cassini Composite Infrared Spectrometer , and would not have been possible without the tireless efforts of the instrument design, operations, and calibration team over more than two decades. LNF was supported by a  Royal Society Research Fellowship and European Research Council   Consolidator Grant  (under the European Union's  Horizon 2020 research and innovation programme , grant agreement No  723890 ) at the  University of Leicester. The UK authors acknowledge the support of the  Science and Technology Facilities Council (STFC). A portion of this work was performed by GSO at the  Jet Propulsion Laboratory, California Institute of Technology , under a contract with  NASA. JAS was supported by the  NASA   Postdoctoral  and  Caltech  programs as well as by a contract with  NASA.
Data availability statement All data can be obtained from the primary author (LNF, email: leigh. fletcher@leicester. ac. uk) upon request, or can be accessed from the following GitHub repository doi:10. 5281/zenodo. 1286856, which contains the temporally and latitudinally averaged spectra used in this study. Raw and calibrated Cassini Composite Infrared Spectrometer observations are available from NASA's Planetary Data System (PDS). The entire CIRS database was used in this study, but we provide unique data identifiers where data subsets were used in our figures. The NEMESIS spectral retrieval tool is available upon reasonable request from P. G. J. Irwin (patrick. irwin@physics. ox. ac. uk). The reconstructed temperature and hydrocarbon fields are also available at the DOI listed above.
Abstract. Headwater streams represent a substantial proportion of river systems and many of them have intermittent flows due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate over time the daily probability of drying (defined at the regional scale). Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence.
The robustness of the models was tested using an independent, dense regional dataset of intermittence observations and observations of the year 2017 excluded from the calibration. The resulting models were used to extrapolate the daily regional probability of drying in France: (i) over the period 2011-2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989-2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level. The two empirical regression models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest.
, 2014; Datry et al. , 2016b)  and could be used for hydrological model calibration  (van Meerveld et al. , 2017). In France,  Datry et al. (2016a)  used such data to describe the spatio-temporal dynamics of aquatic and terrestrial habitats within five river catchments located in the western part of France. They showed that processes resulting in flow intermittence were complex at a fine scale and could vary substantially among nearby catchments. However, these data were only available in a few catchments, limiting any at-tempt to map large-scale patterns of flow intermittence in river networks. Since this first attempt, new sources of observational data have become available in France thanks to the ONDE network (Observatoire National des Etiages, https: //onde. eaufrance. fr, last access: 22 May 2018).
The main objective of this paper is to use discrete (in space and time) field observations of flow intermittence to extrapolate over time the daily probability of drying (averaged at the regional scale). We first carried out a quantitative analysis of the ONDE network data in order to characterise the information that they contribute in comparison with the data resulting from the conventional hydrological monitoring. Then, we developed two empirical models based on linear or logistic regressions to convert discontinuous series of flow intermittence observation from ONDE into continuous daily probability of drying, defined at the regional scale across France. Explanatory variables were derived from available continuous daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using the ONDE discrete observations.
The robustness of the models was tested using (1) an independent, dense regional dataset of intermittence observations and (2) observations of the year 2017 excluded from the calibration. Finally, the resulting models were used to extrapolate the regional probability of drying in France: (i) over the period 2012-2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989-2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level.
ONDE dataset discrete national flow-state observations The ONDE network was set up in 2012 by the French Biodiversity Agency (AFB, formerly ONEMA) with the aim of constituting a perennial network recording summer low-flow levels and used to anticipate and manage water crisis during severe drought events  (Nowak and Durozoi, 2012). There are 3300 ONDE sites distributed throughout France (Fig. 1 ). ONDE sites are located on headwater streams with a Strahler order of strictly less than 5 and balanced across HER2 regions to take into account the representativeness of the hydrological contexts  (Nowak and Durozoi, 2012). The ONDE network is stable over time. Observations have been made monthly (around the 25th) by trained AFB staff, between April and September, every year since 2012. One of the statuses is assigned at each observation among "visible flow", "no visible flow" and "dried out".
hydro. eaufrance. fr, last access: 22 May 2018) French river flow monitoring network. The ONDE sites and a set of 1600 gauging stations available in the HYDRO database have been projected on the RHT (Theoretical Hydrographic Network;  Pella et al. , 2012)  river network and the drainage area and the elevation have been estimated. A large part of ONDE sites are located on small headwater streams, with 70 % of the sites with a drainage area of less than 50 km 2 , while most of the gauging stations record flows of catchments of medium size (between 100 and 500 km 2 ). Only four stations display a drainage area of more than 1000 km 2. The distributions of elevation of the two databases look similar. The ONDE sites are mostly located on rivers with an elevation below 200 m (75 % of sites). The ONDE sites are sparse at high elevations (95 sites located above 1000 m).
This bias is likely due to access difficulties in mountainous areas. tween June and October, resulting in eight observations per year. Four intermittency statuses were available in the POC dataset  (Datry et al. , 2016a) , but to allow comparisons with the ONDE network, we pooled the two "Flowing" and "Low Flow" POC statuses into a single "Flowing" status and the two "No flow" and "Dry" statuses into the "Drying" status. This dataset is available as maps with flow states assigned to the inspected streams. Values of RPoD at each POC observation date are calculated in the same way as RPoD ONDE. RPoD ONDE (d) = (N drying ) HER2-HR (N flowing + N drying ) HER2-HR , (1) Thus RPoD POC is given by the ratio between the number of drying statuses and the total number of observations at each inspected stream located in the same HER2-HR.