Sensitivity Analysis of Transportation Production Costs in Indonesia

The transportation production cost (TPC) considerably has strong influence to the national economic condition. This paper focused on the analysis of the transportation production cost sensitivity in relation to the variation of the external affecting factor, which are fuel price, rupiah exchange rate and Bank of Indonesia interest rate. Based on the R2 values, the TPC components in general have significant correlation, with the fuel prices. However, they do not have high correlation to the fluctuation of interest rate and rupiah exchange rate. The sensitivity analysis shows that a 10% rise on fuel price would cause 6%, 2%, 7%, 2.4%, and 4.9% rise on the TPC of intercity bus, ferry ship, interisland ship, train, and airline, respectively

The Value of Third-Party Certification of Preconditioning Claims at Iowa Feeder Cattle Auctions

After controlling a variety of feeder cattle characteristics and market and sale conditions, we estimate the price premiums for preconditioning (vaccinations and minimum 30 days weaning) claims with and without third-party certification (TPC) as $6.15/cwt and$3.40/cwt, respectively, in Iowa feeder cattle auctions. These premiums differ statistically (p-value less than 0.0001) and their difference exceeds the additional participation cost of TPC ($1/cwt) on average. This indicates that the third party certification is valued in the market to credibly signal preconditioning investment under asymmetric information.

SENSITIVITY ANALYSIS OF TRANSPORTATION PRODUCTION COSTS IN INDONESIA

Abstract The transportation production cost (TPC) considerably has strong influence to the national economic condition. This paper focused on the analysis of the transportation production cost sensitivity in relation to the variation of the external affecting factor, which are fuel price, rupiah exchange rate and Bank of Indonesia interest rate. Based on the R2 values, the TPC components in general have significant correlation, with the fuel prices. However, they do not have high correlation to the fluctuation of interest rate and rupiah exchange rate. The sensitivity analysis shows that a 10% rise on fuel price would cause 6%, 2%, 7%, 2.4%, and 4.9% rise on the TPC of intercity bus, ferry ship, interisland ship, train, and airline, respectively.Keywords: sensitivity analysis, transportation production cost, external affecting factor

SENSITIVITY ANALYSIS OF TRANSPORTATION PRODUCTION COSTS IN INDONESIA

Abstract The transportation production cost (TPC) considerably has strong influence to the national economic condition. This paper focused on the analysis of the transportation production cost sensitivity in relation to the variation of the external affecting factor, which are fuel price, rupiah exchange rate and Bank of Indonesia interest rate. Based on the R2 values, the TPC components in general have significant correlation, with the fuel prices. However, they do not have high correlation to the fluctuation of interest rate and rupiah exchange rate. The sensitivity analysis shows that a 10% rise on fuel price would cause 6%, 2%, 7%, 2.4%, and 4.9% rise on the TPC of intercity bus, ferry ship, interisland ship, train, and airline, respectively.Keywords: sensitivity analysis, transportation production cost, external affecting factor

The state of SQL-on-Hadoop in the cloud

Managed Hadoop in the cloud, especially SQL-on-Hadoop, has been gaining attention recently. On Platform-as-a-Service (PaaS), analytical services like Hive and Spark come preconfigured for general-purpose and ready to use. Thus, giving companies a quick entry and on-demand deployment of ready SQL-like solutions for their big data needs. This study evaluates cloud services from an end-user perspective, comparing providers including: Microsoft Azure, Amazon Web Services, Google Cloud, and Rackspace. The study focuses on performance, readiness, scalability, and cost-effectiveness of the different solutions at entry/test level clusters sizes. Results are based on over 15,000 Hive queries derived from the industry standard TPC-H benchmark. The study is framed within the ALOJA research project, which features an open source benchmarking and analysis platform that has been recently extended to support SQL-on-Hadoop engines. The ALOJA Project aims to lower the total cost of ownership (TCO) of big data deployments and study their performance characteristics for optimization. The study benchmarks cloud providers across a diverse range instance types, and uses input data scales from 1GB to 1TB, in order to survey the popular entry-level PaaS SQL-on-Hadoop solutions, thereby establishing a common results-base upon which subsequent research can be carried out by the project. Initial results already show the main performance trends to both hardware and software configuration, pricing, similarities and architectural differences of the evaluated PaaS solutions. Whereas some providers focus on decoupling storage and computing resources while offering network-based elastic storage, others choose to keep the local processing model from Hadoop for high performance, but reducing flexibility. Results also show the importance of application-level tuning and how keeping up-to-date hardware and software stacks can influence performance even more than replicating the on-premises model in the cloud.This work is partially supported by the Microsoft Azure for Research program, the European Research Council (ERC) under the EUs Horizon 2020 programme (GA 639595), the Spanish Ministry of Education (TIN2015-65316-P), and the Generalitat de Catalunya (2014-SGR-1051).Peer ReviewedPostprint (author's final draft

Methodology for Distributing a VAT

Proposes a revised methodology for analyzing the distributional effects of a value-added tax - the economic burden placed on households of different income levels and demographics - as well as on government revenues and spending and capital