Summary Statistics Sample Clauses

Summary Statistics. Table 2, Panel A reports the summary statistics of fund manager and fund attributes for the full sample. The mutual fund managers’ age distribution is similar to that of earlier papers, with a standard deviation of 9.38, but the average age of 46.2 is higher by 2 to 3 years. On average, the manager level termination probability is 13%, which is lower than what previous literature finds based on fund level termination. Fund managers whose age is above 60 amount to 9% of the fund manager population. Female fund managers also consist of 9% of the total population, and about 60% (56%) of the fund managers have CFA (MBA) degree. Net inflows to funds are on average 7%, with a median value of negative 5%. My main variable of interest, Tracking Error, has a mean of 1.19% (1.41%) with 0.7% 10The data on Active Share is available from the website of Xxxxx Xxxxxxxxx at xxxx://xxx.xxxxxxxxx.xxx/data.html (0.99%) standard deviation at a monthly frequency when estimated using Xxxx-Xxxxxx- Xxxxxxx 4 Factor model (One Factor model with combination of Objective index and S&P 500 as factor returns). The distribution of log fund TNA is highly skewed, as evidenced in the literature, with a mean of 19.55 and standard deviation of 1.64. The log of fund family TNA is also highly skewed, with a mean of 23.32 and a standard deviation of 2.23. Panel B (C) reports the same statistics for a subset of junior (senior) fund managers and their funds. Junior (senior) fund managers are defined as managers with age in the bottom (top) 40th percentile of each cross section. The age gap between average fund manager in the junior group and in the senior group is 18 years. Other notable differences are that funds managed by junior managers receive higher net inflows than the funds managed by seasoned managers. Also, on average, junior fund managers tend to have higher Tracking Error. Panel D (E) reports summary statistics for funds during the the earlier period (more recent period). Most of the fund manager and fund attributes have changed significantly between these two periods. The most notable difference is the increase in termination probability. While the termination probability at an annual basis was 7% during the earlier period, it has become 14%in the more recent period. Also, average net inflows have de- creased from 14% in the earlier period to 5%in the more recent period. Lastly, the measure of risk taking has decreased for both measures of Tracking Error.
Sample 1
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Summary Statistics. Table 2.1 depicts the summary statistics. On average the value of a country's sectoral exports amounts to 5,761,478 US$ per year and is led by China, which has an average export value above 1 billion US$ in the "Electrical and Machinery" sector for the year 2013 until 2015. Our variable of interest, a sectoral productivity shock in a country due to disruptions transmitted over the supply chain, lies between 0 and 1 with an average value of 0.399 for a country, sector and year. The proxy for foreign competition, measured as output weighted disasters abroad per sector, country and year, varies between 0.061 and 0.824, where the maximum of a foreign competition shock is in the "Electricity, Gas and Water" sector in the year 1997. Finally, a sector's size and export experience might affect its ability to cope with a productivity shock transmitted over the supply chain. The gross output of a given sector, which serves as a measure of sectoral size, is led by China's "Electrical and Machinery" sector. Our measure of export experience, a country's sector exports relative to the world exports in the previous year, is on average 1% and lead by France's "Electricity, Gas and Water" sector, which had an export share of around 54% in the year 1996. In Table 2.2 the number of observations per world region and sectoral group are shown. The manufacturing sector is in all world regions the sector where most countries are active each year, which is then followed by the agricultural sector. The energy sector is the least traded sector. All in all, Table 2.2 makes us confident that we have enough observations per country, 32 xxxxx://xxx.xxxxx.xx/ sector and year to identify the impact of supply chain shocks on a country sector's export performance.
Sample 1
Summary Statistics. ‌ The test statistic for hypothesis testing is a quantity derived from the sample in or- der to measure the compatibility between the null hypothesis and the sample data, and determine whether this null hypothesis should be rejected or not. Test statistics developed from a likelihood ratio are optimally powerful according to the Xxxxxx- Xxxxxxx lemma, under certain conditions. Other types of test statistics, however, may also be useful even if not theoretically optimal. A statistic that is interpretable and captures the differences between the observed data and the null-hypothesized models may indeed be useful. Conventionally, hypothesis testing utilizes test statistics whose exact or approximate theoretical null distribution is known under certain strong assumptions of the data such as normality. The permutation test, nevertheless, has an important property of allowing the use of non-standard test statistics with unknown or complicated null distribution (Xxxxxxx et al., 2014). Owing to this key feature of permutation test, we also considered employing the useful whole-image summary statistics as test statistics in addition to cluster statistics for the analysis of the imaging data: the unweighted (h2) and variance-weighted (wh2) averages of all voxel-wise heritability estimates, the second (Q2, the median) and third (Q3) quartiles of these estimates, mean of those heritability estimates greater than Q2 (h2(Q2)), and mean of those heritability estimates greater than Q3 (h2(Q3)). These statistics emphasize the right “tail” (e.g., we omit the first quartile Q1), as exact-zero h2 values make interpreting the left “tail” difficult. If we assume that there are totally K in-mask voxels within the ROI’s, these mean statistics are defined as follows: h2 = 1 Σ h2, K r K r=1 K wh2 = 1 Σ . σ2, σ2Σ h2, σ2 = 1 Σ σ2, r K r=1 r K r 2(Q ) = #{h2 > Q2} K r=1 2(Q ) = #{h2 > Q3} where σ2 and h2 denote the voxel-wise phenotypic variance and the corresponding r r heritability for voxel r (r = 1, . . . , K). The permutation inference can be implemented rapidly using these summary stat- istics, their empirical null distribution can be formed by permutation test, and the corresponding permutation-based p-values can be obtained using these null distri- butions. The fast implementation of these summary statistics provides a tool for exploring the whole brain quickly and a significant result with p-values less than the given level α implies that there should be some significantly he...
Sample 1
Summary Statistics. Table 1 reports the summary statistics for our main variables. Panels A and B include the country-level variables for country pairs and firm-level variables for foreign partners, respectively. In Panel A, we observe that the average ratio of the number of SOE-involved cross-border alliances between two countries (average 0.304%) is lower than the ratio of the number of alliances with non-SOE partners (average 1.190%). This result is consistent with Xxxxxxx and Xxxx (2017)’s finding in the context of acquisitions as they report that the corporate acquirer deal ratio is higher than the government-controlled acquirer deal ratio. As for the country-level factors which measure the differences between the country-pairs, e.g., “Polity IV democracy diff”, the mean value of such factors shown is zero, which is due to the fact that the country-pair-year observations in our sample include both, for instance, Country A - Country B pair and Country B - Country A pair.23 Panel B shows the characteristics of the firms, which 23 That is, we have both Country A - Country B pair and Country B - Country A pair which represents the deals between these two countries but happened in Country A and Country B, respectively. The variable for the Country A - Country B pair observations is measured as the value in Country A minus Country B, whereas for the Country B - Country A pair observations is the value in Country B minus Country A. are defined as foreign partners in cross-border alliances.24 We observe that around 20% foreign firms are in the same industry as the local partners, and on average, the foreign partners in our sample have around $ 4.521 billion total assets in the year before they form an alliance. Besides, Panel C of Table 1 presents the distribution of cross-border alliance activities across countries. The top 20 countries are reported in descending order by the total number of local SOEs involved in cross-border alliances in a particular country from 1990 to 2018. China has the largest total number of cross-border alliances with local SOEs (718 deals, accounting for 27.23% worldwide), followed by Hungary, Russia, and India. We also notice that some emerging countries are more likely to have SOEs than non-SOEs collaborating with foreign firms. For instance, more than 70% deals in Algeria and Czech involve local SOEs in cross- border alliances, followed by Cuba (63.04%), Hungary (59.43%) and Venezuela (46.05%). In these countries, foreign partners are more likely t...
Sample 1
Summary Statistics. Figure 1 plots the increase in dollar value of net repurchase from 1988 through 2006, while Figure 2 shows the normalized value by the aggregate market capitalization of all firms and that of repurchasing firms in the same time period. Aggregate repurchases peaked in 1999 beginning from the end of 1980s, and then dropped slightly afterwards. However, since 2003 there has been an increase, with the most dramatic increase occurring through 2006. By the end of 2006, the total dollar value of net repurchases had almost tripled from its historical peak in 1999. Similar to Xxxxxxx and Xxxxxxx (2008), we find that the market-cap normalized net repurchase value moves in pace with the stock market and business cycles and also indicates the intensiveness of repurchase activity in the middle and through the end of 1990s and after 2003. Overall, consistent with the literature (x.x. Xxxxxxx and Xxxxxxxx (2002) and Xxxxxxx (2008)), Figures 1 and 2 demonstrate that share repurchases have become an increasingly significant payout mode, even after the dividend tax cut in 2003. In addition, the sharp increase in repurchases since 2003 suggests that the initiation and increase in dividend payments following the Jobs and Growth Tax Relief Reconciliation Act may not have come at the expense of a reduction in share repurchases. Figure 3 plots the proportion of firms that make open-market repurchases by year. We examine separately firms that make repurchases only and firms that engage in both repurchasing shares and paying dividends in a given year. Before 1997, the proportion of firms that made repurchases only does not differ from that of firms that paid out cash through both repurchases and dividends. Yet during 1997-2006, there is a high growth in the fraction of firms that repurchased shares without paying dividends, even though the growth rates vary over time and seem to be correlated with stock market valuations. The evidence in Figure 3 strengthens the finding in Figures 1 and 2 that share repurchases have been an increasingly significant phenomenon. Table 1 provides summary statistics for the 55035 firm-year observations for 6291 firms from 1987 through 2006. As shown in Panel A, an average firm makes net repurchases once every five years. The annual net repurchases are valued at about 3.4% (median 1.9%) of the firm’s market value of equity, 7.3% (median 3.8%) of the firm’s book value of equity, and 3.6% (median 1.8%) of the firm’s book value of total assets. Panel B of...
Sample 1

Related to Summary Statistics

  • PRELIMINARY STATEMENTS Pursuant to that certain Agreement and Plan of Merger, dated as of January 27, 2016 (as amended, supplemented or modified from time to time, including all schedules and exhibits thereto, the “Merger Agreement”), by and among Nexstar Broadcasting Group, Inc., a Delaware corporation, Neptune Merger Sub, Inc., a Virginia corporation and a direct wholly-owned Subsidiary of Nexstar Borrower (the “Merger Sub”) and Media General, Inc., a Virginia corporation (“Media General”), the Nexstar Borrower will acquire (the “Acquisition”) Media General by causing Merger Sub to merge with and into Media General with Media General being the surviving corporation, on the terms and subject to the conditions set forth in the Merger Agreement. The Nexstar Borrower and the VIE Borrowers have requested the applicable lenders to extend credit to the applicable borrowers under various revolving credit facilities (including sub-facilities) and term facilities under a credit agreement with Nexstar Borrower and a credit agreement with each of the Borrower, the Xxxxxxxx Borrower and the Shield Borrowers respectively to finance the Acquisition and the Transaction Expenses and, in connection therewith, to consummate the refinancing of certain credit facilities, including to refinance (i) the loans and borrowings of the Nexstar Borrower under the Fifth Amended and Restated Credit Agreement, dated as of December 3, 2012, by and among the Nexstar Borrower, Nexstar Broadcasting Group, Inc., a Delaware corporation, the lenders from time to time party thereto and Bank of America, N.A. as administrative agent, collateral agent, letter of credit issuer and swing line lender (as amended, supplemented, amended and restated or otherwise modified from time to time, the “Existing Nexstar Credit Agreement”), (ii) the loans and borrowings of the Borrower under the Fourth Amended and Restated Credit Agreement, dated as of December 3, 2012, by and among the Borrower, the lenders from time to time party thereto and Bank of America, N.A. as administrative agent and collateral agent (as amended, supplemented, amended and restated or otherwise modified from time to time, the “Existing Mission Credit Agreement”), (iii) the loans and borrowings of Xxxxxxxx Broadcasting Group, Inc., a Texas corporation (the “Xxxxxxxx Borrower”) under the Credit Agreement dated as of December 1, 2014 by and among the Xxxxxxxx Borrower, the lenders from time to time party thereto and Bank of America, N.A. as the administrative agent, the collateral agent and the letter of credit issuer (as amended, supplemented, amended and restated or otherwise modified from time to time, the “Existing Xxxxxxxx Credit Agreement”), (iv) the loans and borrowings of WXXA-TV LLC, a Delaware limited liability company and WLAJ-TV LLC, a Delaware limited liability company (collectively, the “Shield Borrowers”) under the Credit Agreement dated as of July 31, 2013 by and among the Shield Borrowers, Shield Media LLC, a Delaware limited liability company and Shield Lansing LLC, a Delaware limited liability company (collectively, the “Shield Holdings”), the lenders from time to time party thereto, and Royal Bank of Canada, as the administrative agent and the collateral agent (the “Existing Shield Credit Agreement”) and (v) the loans and borrowings of Media General under the Amended and Restated Credit Agreement dated as of July 31, 2013 by and among Media General, the guarantors from time to time party thereto, the lenders from time to time party thereto, and Royal Bank of Canada, as the administrative agent, the letter of credit issuer, the swing line lender and the collateral agent (the “Existing Media General Credit Agreement”). The Nexstar Borrower has agreed to guarantee, and cause Nexstar Media and certain of its Subsidiaries to guarantee, the obligations of each VIE Borrower under the applicable VIE Credit Agreement and certain hedging/cash management obligations of each such VIE Borrower. To the extent required under the Nexstar Credit Agreement, each VIE Borrower has agreed to guarantee, and cause certain of its Restricted Subsidiaries to guarantee, the Nexstar Borrower’s obligations under the Nexstar Credit Agreement and certain hedging/cash management obligations of the Nexstar Borrower. The lenders to the Nexstar Borrower and the lenders to each of the VIE Borrowers have agreed that (i) certain commitments and/or loans of the same Class under the applicable Group Credit Agreements shall be held on a pro rata basis among lenders of the applicable Class under such Group Credit Agreements, (ii) certain voting rights under the Group Credit Agreements shall be exercised on an aggregated basis among the lenders under the Group Credit Agreements, (iii) after the exercise of any remedy under any Group Credit Agreement or other Group Loan Document, all payments received by the Group Lenders shall be applied in accordance with the Intercreditor Agreement Among Group Lenders and (iv) they shall be otherwise bound by the terms of the Intercreditor Agreement Among Group Lenders. In consideration of the mutual covenants and agreements herein contained, the parties hereto covenant and agree as follows:

  • PRELIMINARY STATEMENT (Terms used but not defined in this Preliminary Statement shall have the meanings specified in Article I hereof) The Depositor intends to sell pass-through certificates to be issued hereunder in multiple classes which in the aggregate will evidence the entire beneficial ownership interest in the Trust Fund consisting primarily of the Mortgage Loans (including, in the case of the One Court Square Mortgage Loan, the One Court Square Trust REMIC Regular Interests). As provided herein, the Certificate Administrator will elect that two segregated portions of the Trust Fund (other than the Class A-S Specific Grantor Trust Assets, the Class B Specific Grantor Trust Assets, any Excess Interest Grantor Trust Assets, the Class C Specific Grantor Trust Assets, the Class EC Specific Grantor Trust Assets and the proceeds of the foregoing) be treated for federal income tax purposes as two separate REMICs (designated as the “Upper-Tier REMIC” and the “Lower-Tier REMIC”, respectively). The Regular Certificates and the Class EC Regular Interests will represent “regular interests” in the Upper-Tier REMIC, and the Upper-Tier Residual Interest will be the sole class of “residual interests” in the Upper-Tier REMIC. There are also (i) 12 classes of uncertificated Lower-Tier Regular Interests issued under this Agreement (designated as the Class XX-0, Xxxxx XX-0, Class LA-3, Class LA-4, Class LA-AB, Class LA-S, Class LB, Class LC, Class LD, Class LE, Class LF and Class LG Interests), each of which will constitute a class of “regular interests” in the Lower-Tier REMIC, and (ii) the Lower-Tier Residual Interest, which will be the sole class of “residual interests” in the Lower-Tier REMIC. The Lower-Tier Regular Interests will be held by the Trustee as assets of the Upper-Tier REMIC. The Class R Certificates will represent both the Lower-Tier Residual Interest and the Upper-Tier Residual Interest. In addition, on October 13, 2015, NREC formed the One Court Square REMIC with respect to part of the One Court Square Loan Combination, which issued three pro rata and pari passu regular interests (the “One Court Square REMIC A-1 Regular Interest”, the “One Court Square REMIC A-2 Regular Interest” and the “One Court Square REMIC A-3 Regular Interest (each, a “One Court Square REMIC Regular Interest”, and collectively, the “One Court Square REMIC Regular Interests”). Each One Court Square REMIC Regular Interest has a principal balance set forth below and for tax reporting purposes will be entitled to principal and interest and any other amounts payable on the One Court Square REMIC Regular Interest in the same proportion that its principal balance bears to the aggregate principal balance all of the One Court Square REMIC Regular Interests, as set forth below: One Court Square REMIC Regular Interest Corresponding One Court Square promissory note(s) Initial Principal Balance One Court Square REMIC A-1 Regular Interest One Court Square Promissory Note A-1 $50,000,000 One Court Square REMIC A-2 Regular Interest One Court Square Promissory Note X-0, Xxx Xxxxx Xxxxxx Xxxxxxxxxx Xxxx X-0 $95,000,000 One Court Square REMIC A-3 Regular Interest One Court Square Promissory Note X-0, Xxx Xxxxx Xxxxxx Xxxxxxxxxx Xxxx X-0 $90,000,000 Each One Court Square REMIC Regular Interest holder will be the owner of a percentage interest, specified below, in its corresponding One Court Square Promissory Note(s) other than for tax reporting purposes. The promissory note designated as “Note A-5” (the “One Court Square Promissory Note A-5”), which evidences the One Court Square Mortgage Loan and will be contributed to the Trust, represents a 21.0526% ownership interest in the One Court Square REMIC A-2 Regular Interest and a 22.2222% ownership interest in the One Court Square REMIC A-3 Regular Interest. The promissory note designated as “Note A-1” (the “One Court Square Promissory Note A-1”), which evidences one of the One Court Square Companion Loans and is not an asset of the Trust, evidences 100.0000% ownership of the One Court Square REMIC A-1 Regular Interest. The promissory note designated as “Note A-2” (the “One Court Square Promissory Note A-2”), which evidences one of the One Court Square Companion Loans and is not an asset of the Trust, evidences 78.9474% ownership of the One Court Square REMIC A-2 Regular Interest. The promissory note designated as “Note A-3” (the “One Court Square Promissory Note A-3”), which evidences one of the One Court Square Companion Loans and is not an asset of the Trust, evidences 77.7778% ownership of the One Court Square REMIC A-3 Regular Interest. The promissory note designated as “Note A-4” (the “One Court Square Promissory Note A-4”), which evidences one of the One Court Square Companion Loans and is not an asset of the Trust and does not represent an ownership interest in any of the One Court Square REMIC Regular Interests or the One Court Square REMIC, was contributed to the Outside Securitization Trust related to the One Court Square Mortgage Loan. The residual interest in the One Court Square REMIC is not an asset of the Trust. The parties intend that (i) the portion of the Trust Fund representing the Class A-S Specific Grantor Trust Assets, the Class B Specific Grantor Trust Assets, the Class C Specific Grantor Trust Assets, the Class EC Specific Grantor Trust Assets, any Excess Interest Grantor Trust Assets and the proceeds of the foregoing will be treated as assets of a grantor trust under subpart E of Part I of subchapter J of the Code and (ii) the beneficial interests in such grantor trust will be represented by the Class A-S Certificates, the Class B Certificates, the Class C Certificates, the Class EC Certificates and any Excess Interest Certificates. UPPER-TIER REMIC The following table sets forth the Class designation, the approximate initial pass-through rate and the aggregate initial principal amount (the “Original Certificate Balance”) or, in the case of the Class X-A, Class X-B and Class X-D Certificates, notional amount (the “Original Notional Amount”), as applicable, for each Class of Certificates and each Class EC Regular Interest comprising or evidencing the interests in the Upper-Tier REMIC created hereunder: Class Designation Approximate Initial Pass-Through Rate (per annum) Original Certificate Balance / Original Notional Amount Class A-1 1.700% $13,614,000 Class A-2 2.743% $98,127,000 Class A-3 3.063% $175,000,000 Class A-4 3.329% $221,743,000 Class A-AB 3.127% $31,196,000 Class X-A(1) 1.718% $580,156,000 Class X-B(1) 0.565% $42,404,000 Class A-S Regular Interest 3.585% $40,476,000 Class B Regular Interest 4.271% $42,404,000 Class C Regular Interest 4.836% $38,548,000 Class D 2.804% $44,331,000 Class X-D(1) 2.032% $44,331,000 Class E 4.836% $19,274,000 Class F 4.836% $9,637,000 Class G 4.836% $36,622,163 Class R(2) N/A N/A

  • Statistics 1. Each Party shall provide to the other Party statistics that are required by domestic laws and regulations, and, upon request, other available statistical information as may be reasonably required for the purpose of reviewing the operation of the air services.

  • Usage Statistics The Distributor shall ensure that the Publisher will provide access to both composite system-wide use data and itemized data for the Licensee, the Participating Institutions, individual campuses and labs, on a monthly basis. The statistics shall meet or exceed the most recent project Counting Online Usage of NeTworked Electronic Resources ("COUNTER") Code of Practice Release,3 including but not limited to its provisions on customer confidentiality. When a release of a new COUNTER Code of Practice is issued, the Distributor shall ensure that the Publisher will comply with the implementation time frame specified by COUNTER to provide usage statistics in the new standard format. It is more than desirable that the Standardized Usage Statistics Harvesting Initiative (SUSHI) Protocol4 is available for the Licensee to harvest the statistics.

  • Statistical Analysis 31 F-tests and t-tests will be used to analyze OV and Quality Acceptance data. The F-test is a 32 comparison of variances to determine if the OV and Quality Acceptance population variances 33 are equal. The t-test is a comparison of means to determine if the OV and Quality Acceptance 34 population means are equal. In addition to these two types of analyses, independent verification 35 and observation verification will also be used to validate the Quality Acceptance test results.

  • Statistical Sampling Documentation a. A copy of the printout of the random numbers generated by the “Random Numbers” function of the statistical sampling software used by the IRO.

  • CAUTIONARY STATEMENT Certain statements found in this document may constitute “forward-looking statements” as defined in the U.S. Private Securities Litigation Reform Act of 1995. Such “forward-looking statements” reflect management’s current views with respect to certain future events and financial performance and include any statement that does not directly relate to any historical or current fact. Words such as “anticipate,” “believe,” “expect,” “estimate,” “forecast,” “intend,” “plan,” “project” and similar expressions which indicate future events and trends may identify “forward-looking statements.” Such statements are based on currently available information and are subject to various risks and uncertainties that could cause actual results to differ materially from those projected or implied in the “forward-looking statements” and from historical trends. Certain “forward-looking statements” are based upon current assumptions of future events which may not prove to be accurate. Undue reliance should not be placed on “forward-looking statements,” as such statements speak only as of the date of this document. Factors that could cause actual results to differ materially from those projected or implied in any “forward-looking statement” and from historical trends include, but are not limited to: • economic conditions, including consumer spending and plant and equipment investment in Hitachi’s major markets, particularly Japan, Asia, the United States and Europe, as well as levels of demand in the major industrial sectors Hitachi serves, including, without limitation, the information, electronics, automotive, construction and financial sectors; • exchange rate fluctuations of the yen against other currencies in which Hitachi makes significant sales or in which Hitachi’s assets and liabilities are denominated, particularly against the U.S. dollar and the euro; • uncertainty as to Hitachi’s ability to access, or access on favorable terms, liquidity or long-term financing; • uncertainty as to general market price levels for equity securities, declines in which may require Hitachi to write down equity securities that it holds; • the potential for significant losses on Hitachi’s investments in equity method affiliates; • increased commoditization of information technology products and digital media-related products and intensifying price competition for such products, particularly in the Digital Media & Consumer Products segment; • uncertainty as to Hitachi’s ability to continue to develop and market products that incorporate new technologies on a timely and cost-effective basis and to achieve market acceptance for such products; • rapid technological innovation; • the possibility of cost fluctuations during the lifetime of, or cancellation of, long-term contracts for which Hitachi uses the percentage-of-completion method to recognize revenue from sales; • fluctuations in the price of raw materials including, without limitation, petroleum and other materials, such as copper, steel, aluminum, synthetic resins, rare metals and rare-earth minerals, or shortages of materials, parts and components; • fluctuations in product demand and industry capacity; • uncertainty as to Hitachi’s ability to implement measures to reduce the potential negative impact of fluctuations in product demand, exchange rates and/or price of raw materials or shortages of materials, parts and components; • uncertainty as to Hitachi’s ability to achieve the anticipated benefits of its strategy to strengthen its Social Innovation Business; • uncertainty as to the success of restructuring efforts to improve management efficiency by divesting or otherwise exiting underperforming businesses and to strengthen competitiveness; • uncertainty as to the success of cost reduction measures; • general socioeconomic and political conditions and the regulatory and trade environment of countries where Hitachi conducts business, particularly Japan, Asia, the United States and Europe, including, without limitation, direct or indirect restrictions by other nations on imports and differences in commercial and business customs including, without limitation, contract terms and conditions and labor relations; • uncertainty as to the success of alliances upon which Hitachi depends, some of which Hitachi may not control, with other corporations in the design and development of certain key products; • uncertainty as to Hitachi’s access to, or ability to protect, certain intellectual property rights, particularly those related to electronics and data processing technologies; • uncertainty as to the outcome of litigation, regulatory investigations and other legal proceedings of which the Company, its subsidiaries or its equity method affiliates have become or may become parties; • the possibility of incurring expenses resulting from any defects in products or services of Hitachi; • the possibility of disruption of Hitachi’s operations by earthquakes, tsunamis or other natural disasters; • uncertainty as to Hitachi’s ability to maintain the integrity of its information systems, as well as Hitachi’s ability to protect its confidential information or that of its customers; • uncertainty as to the accuracy of key assumptions Hitachi uses to evaluate its significant employee benefit-related costs; and • uncertainty as to Hitachi’s ability to attract and retain skilled personnel. The factors listed above are not all-inclusive and are in addition to other factors contained in other materials published by Hitachi.

  • Monthly Status Reports 19.1.1 During the Operation Period, the Concessionaire shall, no later than 7 (seven) days after the close of each month, furnish to the Authority and the Independent Engineer a monthly report stating in reasonable detail the condition of the Project including its compliance or otherwise with the Maintenance Requirements, Maintenance Manual, Maintenance Program and Safety Requirements, and shall promptly give such other relevant information as may be required by the Independent Engineer or the Authority. In particular, such report shall separately identify and state in reasonable detail the defects and deficiencies that require rectification.

  • Table 2 (definition of “Casino Gross Revenue”) 15(e) 2 (definition of “Commissioning”) 19 2 (definition of “Committee’s Nominated Representative) 20(1) 6(1)(c) 20(2) 7(8)(a) 21(d) 11(1) 21(e) 11(2) 22(2) 11(3) 23(b) 14(d) 33(2) 15(a)(B) 35(1) 15(b)(i) 35(2) 15(c) 36(b) 15(d) 36(c)

  • Statistical Information Any third-party statistical and market-related data included in the Registration Statement, the Time of Sale Disclosure Package and the Prospectus are based on or derived from sources that the Company believes to be reliable and accurate in all material respects.

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