Trade Liberalization, Heterogeneous Firms and Industrial Dynamics

This master thesis studies how trade liberalization affects the firm-level productivity and industrial evolution. To do so, I built a dynamic model that considers firm-level productivity as endogenous to investigate the influence of trade on firm’s productivity and the market structure. In the framework, heterogeneous firms in the same industry operate differently in equilibrium. Specifically, firms are ex ante identical but heterogeneity arises as an equilibrium outcome. Under the setting of monopolistic competition, this type of model yields an industry that is represented not by a steady-state outcome, but by an evolution that rely on the decisions made by individual firms. I prove that trade liberalization has a general positive impact on technological adoption rates and hence increases the firm-level productivity. Besides, this endogenous technology adoption model also captures the stylized facts: exporting firms are larger and more productive than their non-exporting counterparts in the same sector. I assume that the number of firms is endogenous, since, according to the empirical literature, the industrial evolution shows considerably different patterns across countries; some industries experience large scale of firms’ exit in the period of contracting market shares, while some industries display relative stable number of firms or gradually increase quantities. The special word “shakeout” is used to describe the dramatic decrease in the number of firms. In order to explain the causes of shakeout, I construct a model where forward-looking firms decide to enter and exit the market on the basis of their state of technology. In equilibrium, firms choose different dates to adopt innovation which generate a gradual diffusion process. It is exactly this gradual diffusion process that generates the rapid, large-scale exit phenomenon. Specifically, it demonstrates that there is a positive feedback between firm’s exit and adoption, the reduction in the number of firms increases the incentives for remaining firms to adopt innovation. Therefore, in the setting of complete information, this model not only generates a shakeout but also captures the stability of an industry. However, the solely national view of industrial evolution neglects the importance of international trade in determining the shape of market structure. In particular, I show that the higher trade barriers lead to more fragile markets, encouraging the over-entry in the initial stage of industry life cycle and raising the probability of a shakeout. Therefore, more liberalized trade generates more stable market structure from both national and international viewpoints. The main references are Ederington and McCalman(2008,2009).

International Portfolio Investments and The Informational Value of Trade

A large volume of literature suggests that information asymmetry resulting from the spatial separation between investors and investments have a significant impact on the composition of investors’ domestic and international portfolios. I show that institutional factors affecting trading in tangible goods help explain a substantial portion of investors’ spatial bias. More importantly, I demonstrate that an information flow medium with breadth and richness directly linked to the bilateral commitment of resources between countries, that I measure by their trading intensity in tangible goods, is consistent with the prevailing country allocation in investors’ international portfolios.

The Relay Selection and Transmission Trade-off in Cooperative Communication Systems

A common and practical paradigm in cooperative communication systems is the use of a dynamically selected `best' relay to decode and forward information from a source to a destination. Such systems use two phases - a relay selection phase, in which the system uses transmission time and energy to select the best relay, and a data transmission phase, in which it uses the spatial diversity benefits of selection to transmit data. In this paper, we derive closed-form expressions for the overall throughput and energy consumption, and study the time and energy trade-off between the selection and data transmission phases. To this end, we analyze a baseline non-adaptive system and several adaptive systems that adapt the selection phase, relay transmission power, or transmission time. Our results show that while selection yields significant benefits, the selection phase's time and energy overhead can be significant. In fact, at the optimal point, the selection can be far from perfect, and depends on the number of relays and the mode of adaptation. The results also provide guidelines about the optimal system operating point for different modes of adaptation. The analysis also sheds new insights on the fast splitting-based algorithm considered in this paper for relay selection.

Trade Blocs and the Cold War : The CMEA and the EC challenge, 1969-1976

The coherence of the Soviet bloc was seriously tested at the turn of the 1970s, as the Soviet Union and its allies engaged in intensive negotiations over their relations with the European Communities (EC). In an effort to secure their own national economic interests many East European countries began independent manoeuvres against the wishes of their bloc leader. However, much of the intra-bloc controversy was kept out of the public eye, as the battle largely took place behind the scenes, within the organisation for economic cooperation, the Council for Mutual Economic Assistance (CMEA). The CMEA policy-making process vis-à-vis the EC is described in this study with reference to primary archival materials. This study investigates the negotiating positions and powers of the CMEA member states in their efforts to deal with the economic challenge created by the progress of the EC, as it advanced towards the customs union. This entails an analysis of the functioning principles and performance of the CMEA machinery. The study traces the CMEA negotiations that began in 1970 over its policy toward the EC. The policy was finally adopted in 1974, and was followed by the first official meeting between the two organisations in early 1975. The story ends in 1976, when the CMEA s efforts to enter into working relations with the EC were seemingly frustrated by the latter. The first major finding of the study is that, contrary to much of the prior research, the Soviet Union was not in a hegemonic position vis-à-vis its allies. It had to use a lot of its resources to tame the independent manoeuvring of its smaller allies. Thus, the USSR was not the kind of bloc leader that the totalitarian literature has described. Because the Soviet Union had to spend so much attention on its own bloc-politics, it was not able to concentrate on formulating a policy vis-à-vis the EC. Thus, the Soviet leadership was dependent on its allies in those instances when the socialist countries needed to act as a bloc. This consequently opened up the possibility for the USSR s allies to manoeuvre. This study also argues that when the CMEA did manage to find a united position, it was a force that the EC had to reckon with in its policy-making. This was particularly the case in the implementation of the EC Common Commercial Policy. The other main finding of the study is that, although it has been largely neglected in the previous literature on the history of West European integration, the CMEA did in fact have an effect on EC decision-making. This study shows how for political and ideological reasons the CMEA members did not acknowledge the EC s supranational authority. Therefore the EC had no choice but to refrain from implementing its Common Commercial Policy in full.

A System-C based Micro architectural Exploration Framework for Latency, Power and Performance Trade-offs of On-Chip Interconnection

We describe a System-C based framework we are developing, to explore the impact of various architectural and microarchitectural level parameters of the on-chip interconnection network elements on its power and performance. The framework enables one to choose from a variety of architectural options like topology, routing policy, etc., as well as allows experimentation with various microarchitectural options for the individual links like length, wire width, pitch, pipelining, supply voltage and frequency. The framework also supports a flexible traffic generation and communication model. We provide preliminary results of using this framework to study the power, latency and throughput of a 4x4 multi-core processing array using mesh, torus and folded torus, for two different communication patterns of dense and sparse linear algebra. The traffic consists of both Request-Response messages (mimicing cache accesses)and One-Way messages. We find that the average latency can be reduced by increasing the pipeline depth, as it enables higher link frequencies. We also find that there exists an optimum degree of pipelining which minimizes energy-delay product.

Trade determination in multi-attribute exchanges

Electronic exchanges are double-sided marketplaces that allow multiple buyers to trade with multiple sellers, with aggregation of demand and supply across the bids to maximize the revenue in the market. Two important issues in the design of exchanges are (1) trade determination (determining the number of goods traded between any buyer-seller pair) and (2) pricing. In this paper we address the trade determination issue for one-shot, multi-attribute exchanges that trade multiple units of the same good. The bids are configurable with separable additive price functions over the attributes and each function is continuous and piecewise linear. We model trade determination as mixed integer programming problems for different possible bid structures and show that even in two-attribute exchanges, trade determination is NP-hard for certain bid structures. We also make some observations on the pricing issues that are closely related to the mixed integer formulations.

Performance and variability trade-off with gate-to-source/drain overlap length

The impact of gate-to-source/drain overlap length on performance and variability of 65 nm CMOS is presented. The device and circuit variability is investigated as a function of three significant process parameters, namely gate length, gate oxide thickness, and halo dose. The comparison is made with three different values of gate-to-source/drain overlap length namely 5 nm, 0 nm, and -5 nm and at two different leakage currents of 10 nA and 100 nA. The Worst-Case-Analysis approach is used to study the inverter delay fluctuations at the process corners. The drive current of the device for device robustness and stage delay of an inverter for circuit robustness are taken as performance metrics. The design trade-off between performance and variability is demonstrated both at the device level and circuit level. It is shown that larger overlap length leads to better performance, while smaller overlap length results in better variability. Performance trades with variability as overlap length is varied. An optimal value of overlap length of 0 nm is recommended at 65 nm gate length, for a reasonable combination of performance and variability.

Diversity-Rate Trade-off for Fading Channels with Power Control

We consider a complex, additive, white Gaussian noise channel with flat fading. We study its diversity order vs transmission rate for some known power allocation schemes. The capacity region is divided into three regions. For one power allocation scheme, the diversity order is exponential throughout the capacity region. For selective channel inversion (SCI) scheme, the diversity order is exponential in low and high rate region but polynomial in mid rate region. For fast fading case we also provide a new upper bound on block error probability and a power allocation scheme that minimizes it. The diversity order behaviour of this scheme is same as for SCI but provides lower BER than the other policies.

Threats and trade-fffs in resource critical crowdsourcing tasks over networks

In recent times, crowdsourcing over social networks has emerged as an active tool for complex task execution. In this paper, we address the problem faced by a planner to incen-tivize agents in the network to execute a task and also help in recruiting other agents for this purpose. We study this mecha-nism design problem under two natural resource optimization settings: (1) cost critical tasks, where the planner’s goal is to minimize the total cost, and (2) time critical tasks, where the goal is to minimize the total time elapsed before the task is executed. We define a set of fairness properties that should beideally satisfied by a crowdsourcing mechanism. We prove that no mechanism can satisfy all these properties simultane-ously. We relax some of these properties and define their ap-proximate counterparts. Under appropriate approximate fair-ness criteria, we obtain a non-trivial family of payment mech-anisms. Moreover, we provide precise characterizations of cost critical and time critical mechanisms.

Regenerating codes: A reformulated storage-bandwidth trade-off and a new construction

In this paper, the storage-repair-bandwidth (SRB) trade-off curve of regenerating codes is reformulated to yield a tradeoff between two global parameters of practical relevance, namely information rate and repair rate. The new information-repair-rate (IRR) tradeoff provides a different and insightful perspective on regenerating codes. For example, it provides a new motivation for seeking to investigate constructions corresponding to the interior of the SRB tradeoff. Interestingly, each point on the SRB tradeoff corresponds to a curve in the IRR tradeoff setup. We characterize completely, functional repair under the IRR framework, while for exact repair, an achievable region is presented. In the second part of this paper, a rate-half regenerating code for the minimum storage regenerating point is constructed that draws upon the theory of invariant subspaces. While the parameters of this rate-half code are the same as those of the MISER code, the construction itself is quite different.

Co-benefits, trade-offs, barriers and policies for greenhouse gas mitigation in the agriculture, forestry and other land use (AFOLU) sector

The agriculture, forestry and other land use (AFOLU) sector is responsible for approximately 25% of anthropogenic GHG emissions mainly from deforestation and agricultural emissions from livestock, soil and nutrient management. Mitigation from the sector is thus extremely important in meeting emission reduction targets. The sector offers a variety of cost-competitive mitigation options with most analyses indicating a decline in emissions largely due to decreasing deforestation rates. Sustainability criteria are needed to guide development and implementation of AFOLU mitigation measures with particular focus on multifunctional systems that allow the delivery of multiple services from land. It is striking that almost all of the positive and negative impacts, opportunities and barriers are context specific, precluding generic statements about which AFOLU mitigation measures have the greatest promise at a global scale. This finding underlines the importance of considering each mitigation strategy on a case-by-case basis, systemic effects when implementing mitigation options on the national scale, and suggests that policies need to be flexible enough to allow such assessments. National and international agricultural and forest (climate) policies have the potential to alter the opportunity costs of specific land uses in ways that increase opportunities or barriers for attaining climate change mitigation goals. Policies governing practices in agriculture and in forest conservation and management need to account for both effective mitigation and adaptation and can help to orient practices in agriculture and in forestry towards global sharing of innovative technologies for the efficient use of land resources. Different policy instruments, especially economic incentives and regulatory approaches, are currently being applied however, for its successful implementation it is critical to understand how land-use decisions are made and how new social, political and economic forces in the future will influence this process.

A trade-off between maxima in efficiency and specific work output of super- and trans-critical CO2 Brayton cycles

Several operational aspects for thermal power plants in general are non-intuitive and involve simultaneous optimization of a number of operational parameters. In the case of solar operated power plants, it is even more difficult due to varying heat source temperatures induced by variability in insolation levels. This paper introduces a quantitative methodology for load regulation of a CO2 based Brayton cycle power plant using the `thermal efficiency and specific work output' coordinate system. The analysis shows that a transcritical CO2 cycle offers more flexibility under part load performance than the supercritical cycle in case of non-solar power plants. However, for concentrated solar power, where efficiency is important, supercritical CO2 cycle fares better than transcritical CO2 cycle. A number of empirical equations relating heat source temperature, high side pressure with efficiency and specific work output are proposed which could assist in generating control algorithms. (C) 2015 Elsevier B.V. All rights reserved.

Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-Offs and Optimal Design

Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.