Browsing by Author "Rivera, Nilza"

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    A method to estimate the robustness of the secondary refined copper supply function
    (2023) Rivera, Nilza; Ignacio Guzman, Juan; Lagos, Gustavo
    Knowing the factors that influence the secondary refined copper supply behavior has been fundamental in generating a copper market model and developing public and corporate policies. When analyzing the explanatory variables used in the existing models in the literature, it is possible to observe high variability in estimating the parameters when modifying the availability of information or changing the observation period. Based on this, we argue that only some explanatory variables will have robust estimated parameters, which means that they are unbiased, stable (i.e., they do not vary significantly when the specification of the equation or the number of observations changes), and with asymptotic convergence over time. This work defines and validates a method to select robust explanatory variables capable of quantifying the refined secondary supply of copper (or any other variable) in a given period. Using a database with 23 explanatory variables in the period 1960-2017, we characterize the estimated parameters with high and low robustness, thus supporting the proposed hypothesis. The results obtained allowed identifying those variables with low uncertainty in estimating their parameters, with a high statistical significance, and with a low standard deviation. This allows to obtain a robust function for the secondary refined copper supply in the long term, capturing essential elements of reality.
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    Dynamic relationship between refined and scrap copper prices
    (2024) Rivera, Nilza; Guzman, Juan Ignacio
    In this paper, we explore the relationship between refined and scrap copper prices, considering the possibility that this relationship may vary across various products and over time. Building upon the conjecture put forth by Phillip Crowson (Miner Econ 24(1):1-6, 2011), here referred to as the Crowson Conjecture, our study aims to investigate how the substitution between refined copper and copper scrap No. 1 and No. 2 can impact the prices of each other. To achieve this, we develop a theoretical model that allows us to understand the potential influence of substitution between refined copper and copper scrap No. 1 and No. 2 during different time periods. Additionally, we conduct an empirical test using monthly time series data spanning from January 2004 to June 2022, analyzing structural breaks in these prices. Our empirical analysis successfully identifies three distinct structural breaks: January 2004 to August 2009, September 2009 to July 2017, and August 2017 to June 2022. These breaks serve as critical time periods for measuring Granger causality between the examined prices. Interestingly, our findings indicate that the causal relationships between the refined and scrap copper prices change throughout these three analyzed breaks, providing evidence in support of Crowson Conjecture. By shedding light on the evolving nature of the relationship between refined and scrap copper prices, our study contributes to a deeper understanding of the dynamics within the copper market. These insights have implications for market participants and policymakers, enabling them to make more informed decisions regarding pricing and resource allocation strategies.
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    Evaluation of econometric models of secondary refined copper supply
    (2021) Rivera, Nilza; Ignacio Guzman, Juan; Joaquin Jara, Jose; Lagos, Gustavo
    Copper is essential in attaining a sustainable development path due to its prominent role in the electromobility and renewable energy industries. In 2019 refined copper usage was 23.5 million tons, of which primary copper supplied 86.3%, and the remaining 13.7% was provided by secondary metal. In the future, copper recycling would increase significantly concerning primary copper supply to meet the goal of decreasing greenhouse gases emissions. Secondary copper production reduces energy consumption by 85% and greenhouse gas emissions by 65% compared to average primary sources.