On the feasibility of collaborative green data center ecosystems

The increasing awareness of the impact of the IT sector on the environment, together with economic factors, have fueled many research efforts to reduce the energy expenditure of data centers. Recent work proposes to achieve additional energy savings by exploiting, in concert with customers, service workloads and to reduce data centers’ carbon footprints by adopting demand-response mechanisms between data centers and their energy providers. In this paper, we debate about the incentives that customers and data centers can have to adopt such measures and propose a new service type and pricing scheme that is economically attractive and technically realizable. Simulation results based on real measurements confirm that our scheme can achieve additional energy savings while preserving service performance and the interests of data centers and customers.Peer ReviewedPostprint (author's final draft

Strategies for pricing publicly provided health services

The authors examine how governments finance and allocate public spending, with an eye to developing strategies for pricing publicly provided health services. They also examine the implications of current policy and the possibility for rationalizing competing government priorities. Because governments face budget constraints and cannot fully subsidize all programs and activities, the authors argue the following: a) Public spending on health can (1) improve health outcomes, (2) promote nonhealth aspects of well-being (for example, reducing individuals'risk of economic losses from random health crises), and (3) finance redistribution to the poor. Optimal subsidy and fee policy will depend on how much relative weight government places on those competing objectives. Subsidies need to be reallocated toward the poor and toward public health sector can financed by increasing public subsidies. b) Prices for curative services (user fee) have two distinct roles. They can raise revenue, freeing public resources to be reallocated to public health activities and for limited cofinancing to improve the quality of curative care. More important, they can improve efficiency in the use of public facilities and the health care system as a whole. But those gains must be weighed against evidence that increased fees can compromise public health's three main goals. The literature has focused largely on how raising revenue affects the poor, but the more important effect is likely to be the guidance of resources. User fees are important in cofinancing health care but shouldn't be the primary means of finance. c) Revenue generated from user fees is sometimes used to improve the quality of, and access to, curative medical care. There is some evidence that people are willing to pay some of the cost of improving health care (especially for drugs), but the wealthy are willing to pay a lot more than the poor. If governments charge the average"willingness to pay,"the wealthy will use the services more, the poor, less. d) Prepayment social insurance plans hold promise, but there is evidence that they may introduce inefficient inflation of medical care costs that lower- and middle- income countries cannot afford.Public Sector Economics&Finance,Health Systems Development&Reform,Environmental Economics&Policies,Payment Systems&Infrastructure,Health Economics&Finance,Environmental Economics&Policies,Public Sector Economics&Finance,Health Systems Development&Reform,Health Economics&Finance,Urban Economics

Pricing, production, and persistence.

Though built with increasingly precise microfoundations, modern optimizing sticky price models have displayed a chronic inability to generate large and persistent real responses to monetary shocks, as recently stressed by Chari, Kehoe, and McGrattan [2000]. This is an ironic finding, since Taylor [1980] and other researchers were motivated to study sticky price models in part by the objective of generating large and persistent business fluctuations. ; The authors trace this lack of persistence to a standard view of the cyclical behavior of real marginal cost built into current sticky price macro models. Using a fully-articulated general equilibrium model, they show how an alternative view of real marginal cost can lead to substantial persistence. This alternative view is based on three features of the "supply side" of the economy that we believe are realistic: an important role for produced inputs, variable capacity utilization, and labor supply variability through changes in employment. Importantly, these "real flexibilities" work together to dramatically reduce the elasticity of marginal cost with respect to output, from levels much larger than unity in CKM to values much smaller than unity in this analysis. These "real flexibilities" consequently reduce the extent of price adjustments by firms in time-dependent pricing economies and the incentives for paying fixed costs of adjustment in state-dependent pricing economies. The structural features also lead the sticky price model to display volatility and comovement of factor inputs and factor prices that are more closely in line with conventional wisdom about business cycles and various empirical studies of the dynamic effects of monetary shocks.Prices ; Production (Economic theory)

Variable Factor Utilization and International Business Cycles

When an economic boom produces high output, employment, and investment in the United States, there is usually a simultaneous boom in other industrialized countries. But, why? Answering this question is a central goal of international macroeconomics. However, multi-country dynamic equilibrium models have struggled with two major problems. The first difficulty is that the productivity shocks required by the model are implausibly large and volatile. Second, these models have difficulty explaining why factor inputs move together so closely across countries: realistic international comovement of business cycles requires implausibly high cross-country correlations of productivity shocks. This paper builds a model in which the utilization rates of capital and labor can be varied in response to shocks. We find that variable factor utilization is quite successful in (i) reducing the required size of productivity shocks; and (ii) increasing international comovement of factor inputs, with most of the improvement stemming from variable capital utilization.

Pricing, Production and Persistence

Though built with increasingly precise microfoundations, modern optimizing sticky price models have displayed a chronic inability to generate large and persistent real responses to monetary shocks, as recently stressed by Chari, Kehoe and McGrattan [2000]. This is an ironic finding, since Taylor [1980] and other researchers were motivated to study sticky price models in part by the objective of generating large and persistent business fluctuations. We trace this lack of persistence to a standard view of the cyclical behavior of real marginal cost built into current sticky price macro models. Using both a small loglinear macroeconomic model and a larger fully articulated model, we show how an alternative view of real marginal cost can lead to substantial persistence. This alternative view is based on three features of the 'supply side' of the economy that we believe are realistic: an important role for produced inputs, variable capacity utilization, and labor supply variability through changes in employment. Importantly, these 'real flexibilities' work together to dramatically reduce the elasticity of marginal cost with respect to output, from levels much larger than unity in CKM to values much smaller than unity in our analysis. These 'real flexibilities' consequently reduce the extent of price adjustments by firms in time-dependent pricing economies and the incentives for paying fixed costs of adjustment in state-dependent pricing economies. The structural features also lead the sticky price model to display volatility and comovement of factor inputs and factor prices that are more closely in line with conventional wisdom about business cycles.

Notes on Cloud computing principles

This letter provides a review of fundamental distributed systems and economic Cloud computing principles. These principles are frequently deployed in their respective fields, but their inter-dependencies are often neglected. Given that Cloud Computing first and foremost is a new business model, a new model to sell computational resources, the understanding of these concepts is facilitated by treating them in unison. Here, we review some of the most important concepts and how they relate to each other

Capital Use Intensity and Productivity Biases

Measures of productivity growth are often pro-cyclical. This study focuses on measurement errors in capital inputs, associated with unobserved variations in capital utilization rates, as an explanation for the existence of pro-cyclical patterns in measures of agricultural productivity. Recently constructed national and state-specific indexes of inputs, outputs, and productivity in U.S. agriculture for 1949-2002 are used to estimate production functions in growth rate form that include proxy variables for changes in the utilization of durable inputs. The proxy variables include an index of farmers’ terms of trade and an index of local seasonal growing conditions. We find that utilization responses by farmers are significant and bias measures of productivity growth in a pro-cyclical pattern. We quantify the bias, adjust the measures of productivity for the estimated utilization responses, and compare the adjusted and conventional measures.Productivity Analysis,

A Minimum-Cost Flow Model for Workload Optimization on Cloud Infrastructure

Recent technology advancements in the areas of compute, storage and networking, along with the increased demand for organizations to cut costs while remaining responsive to increasing service demands have led to the growth in the adoption of cloud computing services. Cloud services provide the promise of improved agility, resiliency, scalability and a lowered Total Cost of Ownership (TCO). This research introduces a framework for minimizing cost and maximizing resource utilization by using an Integer Linear Programming (ILP) approach to optimize the assignment of workloads to servers on Amazon Web Services (AWS) cloud infrastructure. The model is based on the classical minimum-cost flow model, known as the assignment model.Comment: 2017 IEEE 10th International Conference on Cloud Computin

Asset Utilization and Bias in Measures of U.S. Agricultural Productivity

A common observation is that measures of productivity growth are pro-cyclical, meaning they are higher (or grow faster) on average during periods of economic expansion than during periods of economic contraction. This study focuses on measurement errors related to capital inputs as an explanation for the existence of pro-cyclical patterns in measures of agricultural productivity. Calculating a time series of capital inputs is difficult and prone to errors. Myriad assumptions are required to construct a typical measure of the capital stock, and further, sometimes related, assumptions must be made about the utilization of the stock to derive a measure of capital service flows. We test the hypothesis that unmeasured changes in the utilization of capital can affect productivity measures. This is accomplished using recently constructed indexes of inputs, outputs, and productivity in U.S. agriculture for 1949-2002. We find that utilization responses by farmers are significant and bias measures of productivity growth in a pro-cyclical pattern. The bias is quantified and the measures of productivity are adjusted for the estimated utilization responses and compared to the original measures.Financial Economics,

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